• Wind and Structures
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• 제22권4호
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• pp.503-524
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• 2016

The suitability of Computational Fluid Dynamics (CFD) simulations on the built environment for the purpose of estimating average roughness characteristics and for studying wind flow patterns within the environment is assessed. Urban models of various levels of complexity are considered including an empty domain, array of obstacles arranged in regular and staggered manners, in-homogeneous roughness with multiple patches, a semi-idealized built environment, and finally a real built environment. For each of the test cases, we conducted CFD simulations using RANS turbulence closure and validated the results against appropriate methods: existing empirical formulas for the homogeneous roughness case, empirical wind speed models for the in-homogeneous roughness case, and wind tunnel tests for the semi-idealized built environment case. In general, results obtained from the CFD simulations show good agreement with the corresponding validation methods, thereby, giving further evidence to the suitability of CFD simulations for built environment studies consisting of wide-ranging roughness. This work also provides a comprehensive overview of roughness modeling in CFD-from the simplest approach of modeling roughness implicitly through wall functions to the most elaborate approach of modeling roughness explicitly for the sake of accurate wind flow simulations within the built environment.

• 한국정보시스템학회지:정보시스템연구
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• 제24권3호
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• pp.21-46
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• 2015

Purpose Social Network Service (SNS) users feel fatigue in process of using open type of SNS like Facebook and Twitter. Compared to the open SNS, the closed SNS takes an closed form to prevent privacy exposure, and they are more practical and advantageous to form deeper social relationships. This study attempt to examine the effects of the mobile closed SNS characteristics (such as usefulness, playfulness, perceived security, psychological privacy, social influence, and belonging) on the users' continuous SNS usage intention. Design/methodology/approach This study used a mixed methodology combining in-depth interviews and empirical validation to investigate the effects of the mobile closed SNS characteristics on the continuous SNS usage intention of users. Findings Analytical results from a survey of 210 mobile closed SNS users showed that except perceived security, the effects of the five SNS characteristics on continuous SNS usage intention were significant. These findings contribute to improving the quality of mobile closed SNS services and suggesting SNS related marketing strategies.

• ETRI Journal
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• 제27권6호
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• pp.747-758
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• 2005

The problem of selection among competing models has been a fundamental issue in statistical data analysis. Good fits to data can be misleading since they can result from properties of the model that have nothing to do with it being a close approximation to the source distribution of interest (for example, overfitting). In this study we focus on the preference among models from a family of polynomial regressors. Three decades of research has spawned a number of plausible techniques for the selection of models, namely, Akaike's Finite Prediction Error (FPE) and Information Criterion (AIC), Schwartz's criterion (SCH), Generalized Cross Validation (GCV), Wallace's Minimum Message Length (MML), Minimum Description Length (MDL), and Vapnik's Structural Risk Minimization (SRM). The fundamental similarity between all these principles is their attempt to define an appropriate balance between the complexity of models and their ability to explain the data. This paper presents an empirical study of the above principles in the context of model selection, where the models under consideration are univariate polynomials. The paper includes a detailed empirical evaluation of the model selection methods on six target functions, with varying sample sizes and added Gaussian noise. The results from the study appear to provide strong evidence in support of the MML- and SRM- based methods over the other standard approaches (FPE, AIC, SCH and GCV).

• 한국실내디자인학회논문집
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• 제23권4호
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• pp.120-128
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• 2014

Due to prolonged recession and limited spending of the consumers, domestic fashion brands are putting their efforts in pursuing competitiveness in order to survive in an intense competition, and because of this reason, VMD is being considered significant as a strategy for store environment improvement. An empirical research regarding analysis for systematic strategic VMD configuration factors of fashion retail store and relationship of repurchase intention that have effects on increase in sales was conducted. Thus, this study considers importance and spatial interrelation of VMD configuration factors of fashion retail store through theoretical consideration, and based on this, VMD configuration factors were restructured into reconcilability, attractiveness and epidemicity. An empirical validation through theoretical hypotheses and survey for relationships among VMD configuration factors, brand preference and repurchase intention was conducted. As a result of path analysis, VMD configuration factors reconcilability, attractiveness and epidemicity have effects on repurchase intention, and it was analyzed that epidemicity has the biggest effect on consumers. Also, it was found that brand preference has effects on repurchase intention and through this, as favorability and customer satisfaction for brand has effects on repurchase intention, it is judged that creating a strong brand image and brand image building is important the most for improving brand preference.

• 정보보호학회논문지
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• 제14권4호
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• pp.61-74
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• 2004

위험분석모델은 정보시스템 보안과 관련된 위험을 자산, 위협, 취약성, 보안통제의 관계를 통해서 설명하는 체계화 된 방법이다. 그러나 위험분석모델의 실증적인 연구가 이루어진 경우는 상당히 드물며, 특히 위험분석모델의 타당성 논의는 거의 없는 실정이다. 구조방정식모델을 적용하여 전자상거래 환경에서 위험분석모델의 타당성에 대한 실증적 분석을 한 결과, 위험의 수준에 영향을 미치는 요인으로 언급되는 위협과 보안통제는 통계적으로 유의한 것으로 나타났다. 본 연구는 전자상거래 이용자의 위험인지에 영향을 미치는 요인을 위험분석 접근법을 이용하여 모델 화하여 검증함으로써 전자상거래 위험에 영향을 미치는 선행요인을 규명할 뿐만 아니라 위험분석접근법을 통한 전자상거래에 대한 새로운 관점에서의 접근을 가능하게 한다.

• 디지털산업정보학회논문지
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• 제19권2호
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• pp.161-175
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• 2023

The purpose of this study is the effects of Social Characteristics and Personal Characteristics on Virtual Asset Purchase Intention. TPB (Theory of Planned Behavior) model is validated as a theoretical background. possessiveness, and innovation tendency, herding, subjective norm, attitude, and Purchase intention were composed of variables. The method of the study collected 474 data of those experienced in NFT through a survey and conducted as a structural equation modeling method using AMOS. The result of this paper shows that 4 hypotheses are accepted statistically significant except 1 hypotheses among 5 hypotheses. Therefore, this study demonstrated the factors that influence the purchase intention of non-fungible tokens. This study concluded that possessiveness, herding, subjective norm, attitude had a statistically significant effect on Purchase intention. NFT research is just getting started, and there are not many empirical studies targeting investors, interested people, and companies. In this respect, this study will be able to provide useful information for NFT research.

• Journal of Forest and Environmental Science
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• 제28권4호
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• pp.205-211
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• 2012

Yield tables are a frequently used data base for regional timber resource forecasting. A normal yield table is based on two independent variables, age and site (species constant), and applies to fully stocked (or normal) stands while empirical yield tables are based on average rather than fully stocked stands. Normal and empirical yield tables essentially have many limitations. The limitations of normal and empirical yield tables led to the development of variable density yield tables. Mathematical models for estimating timber yields are usually developed by fitting a suitable equation to observed data. The model is then used to predict yields for conditions resembling those of the original data set. It may be accurate for the specific conditions, but of unproven accuracy or even entirely useless in other circumstances. Thus, these models tend to be specific rather than general and require validation before applying to other areas. Dalbergia sissoo forms a major portion of irrigated plantations in the hot desert of India and is an important timber tree species where stem wood is primarily used as timber. Variable density yield model is not available for this species which is very crucial in long-term planning for managing the plantations on a sustained basis. Thus, the objective of this study was to develop variable density yield model based on the data collected from 30 sample plots of D. sissoo laid out in IGNP area of Rajasthan State (India) and measured annually for 5 years. The best approximating model was selected based on the fit statistics among the models tested in the study. The model develop was evaluated based on quantitative and qualitative statistical criteria which showed that the model is statistically sound in prediction. The model can be safely applied on D. sissooo plantations in the study area or areas having similar conditions.

• 한국도로학회논문집
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• 제4권3호
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• pp.1-13
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• 2002

현재 도로 설계는 기존의 경험적인 설계법에서 역학적인 설계법으로 바뀌고 있는 추세이다. 이러한 전환기에서 세계 많은 도로국들은 역학적-경험적인 도로 설계법을 개발하고 있고 혹은 이미 채택하여 적용하고 있다. 이에 실제 미국 미시간 도로국에서 나온 자료를 바탕으로 역학적-경험적 설계법을 개발하였다. 이 역학적-경험적 설계법의 연결 함수 (transfer function)로 사용될 소성 변형 예측 모델과 피로 균열 예측 모델도 함께 개발되었다. 여기서는 이 설계법을 개발하는데 사용된 자료와 예측 모델, 설계 알고리듬등이 소개된다. 이 설계법의 검증을 위해 기존의 경험적 설계법에 의한 설계와 새로 제시된 설계법에 의한 설계가 비교된다. 새로 설계된 설계법은 설계자 혹은 사용자가 도로 파손의 기준을 정량적으로 정함으로서 좀더 구체적으로 설계를 할 수가 있다.

• 한국추진공학회지
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• 제24권6호
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• pp.143-154
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• 2020

액체로켓엔진의 추진제 공급시스템의 각 요소와 전체 시스템에 대한 보편적 모델에 실험계수를 적용한 수학적 모델링 기법을 소형 액체로켓엔진을 모사한 수류 시험 장치를 통한 실험 결과로부터 검증하였다. 유체저항요소와 펌프의 압력 변화에 대한 예측을 수행하였으며 예측 정확도 향상을 위해 구성요소 모델링에 대하여 실험계수를 적용하였다. 이를 위해 각 구성요소에 대해 유동의 지배방정식이나 이미 알려진 경험식을 기반으로 실험계수의 도출 방안에 대하여 정리하였으며 사용한 상용품의 실험계수를 제시하였다. 모델링을 통한 예측 결과는 실험 데이터와 비교적 잘 일치하였다. 실험데이터와의 검증을 통해 시뮬레이션의 정확도에 영향을 미치는 인자에 대해 분석하고 시스템 해석의 정확도 향상 방안에 대하여 제안하였다.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2020년도 학술발표회
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• pp.172-172
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• 2020

In recent years, soil erosion has come to be regarded as an essential environmental problem in human life. Soil erosion causes various on- and off-site problems such as ecosystem destruction, decreased agricultural productivity, increased riverbed deposition, and deterioration of water quality in streams. To solve these problems caused by soil erosion, it is necessary to quantify where, when, how much soil erosion occurs. Empirical erosion models such as the Universal Soil Loss Equation (USLE) family models have been widely used to make spatially distributed soil erosion vulnerability maps. Even if the models detect vulnerable sites relatively well by utilizing big data related to climate, geography, geology, land use, etc. within study domains, they do not adequately describe the physical process of soil erosion on the ground surface caused by rainfall or overland flow. In other words, such models remain powerful tools to distinguish erosion-prone areas at the macro scale but physics-based models are necessary to better analyze soil erosion and deposition and eroded particle transport. In this study, the physics-based Surface Soil Erosion Model (SSEM) was upgraded based on field survey information to produce sediment yield at the watershed scale. The modified model (hereafter MoSE) adopted new algorithms on rainfall kinematic energy and surface flow transport capacity to simulate soil erosion more reliably. For model validation, we applied the model to the Doam dam watershed in Gangwon-do and compared the simulation results with the USLE outputs. The results showed that the revised physics-based soil erosion model provided more improved and reliable simulation results than the USLE in terms of the spatial distribution of soil erosion and deposition.