• Proceedings of the Korean Association for Survey Research Conference
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• 2000.06a
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• pp.105-112
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• 2000

대부분 통계조사에서 흔히 발생하는 무응답을 처리하기 위한 방법으로 최근에는 표본 대체 방법이 널리 이용되고 있다. 본 논문에서는 여러 가지 표본 대체 방법을 소개하고 각 방법의 장. 단점을 비교. 설명한다. 그리고 대체된 데이터를 응답 데이터인 것처럼 활용했을 때 발생하는 문제점들을 지적하고 모의 실험을 통하여 그 정도를 살펴본다. 이와 더불어 제기된 문제점을 해결하는 몇 가지 해결방안을 소개한다.

• Proceedings of the Korea Society for Energy Engineering kosee Conference
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• 2003.05a
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• pp.37-62
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• 2003

대체에너지는 지속 가능한 에너지공급원으로 21세기 유망산업으로 등장, 환경문제와 에너지 안보를 동시에 충족, 수출전략산업으로 육성할 필요가 증대, Johannesburg의 지속 가능발전정상회의(WSSD) 재생에너지 비중 확대 논의(미국과 EU의 대립) 대체에너지 공급 목표 설정에는 실패, 대체에너지의 위상 크게 향상(중략)

• The Magazine of the Society of Air-Conditioning and Refrigerating Engineers of Korea
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• v.32 no.4
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• pp.17-21
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• 2003

대체에너지는 과다한 초기투자의 장애요인에도 불구하고 화석에너지의 고갈문제와 환경문제에 대한 핵심 해결방안이라는 점에서 선진 각 국에서는 대체에너지에 대한 과감한 연구개발과 보급정책 등을 추진해오고 있다. 본 고에서는 대체에너지의 기술개발 및 정책 전망에 대해서 기술하고자 한다.

• The Journal of Korean Academic Society of Nursing Education
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• v.11 no.1
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• pp.86-93
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• 2005

• The Magazine for Energy Service Companies
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• s.17
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• pp.40-51
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• 2002

• The Korean Society of Law and Medicine
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• v.6 no.1
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• pp.153-164
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• 2005

• The Korean Journal of Applied Statistics
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• v.32 no.4
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• pp.543-559
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• 2019

Data often include missing values due to various reasons. If the missing data mechanism is not MCAR, analysis based on fully observed cases may an estimation cause bias and decrease the precision of the estimate since partially observed cases are excluded. Especially when data include many variables, missing values cause more serious problems. Many imputation techniques are suggested to overcome this difficulty. However, imputation methods using parametric models may not fit well with real data which do not satisfy model assumptions. In this study, we review imputation methods using nonlinear models such as kernel, resampling, and spline methods which are robust on model assumptions. In addition, we suggest utilizing imputation classes to improve imputation accuracy or adding random errors to correctly estimate the variance of the estimates in nonlinear imputation models. Performances of imputation methods using nonlinear models are compared under various simulated data settings. Simulation results indicate that the performances of imputation methods are different as data settings change. However, imputation based on the kernel regression or the penalized spline performs better in most situations. Utilizing imputation classes or adding random errors improves the performance of imputation methods using nonlinear models.

• Korean Journal of Food Science and Technology
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• v.52 no.6
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• pp.641-648
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• 2020

The objective of this study was to optimize the mixing ratio of mixed bean protein concentrate (MBPC) and to improve the quality of sausage analogues. Soybean (Glycine max MERR), mung bean (Phaseolus radiatus L.), red bean [Vigna angularis (Wild.)], and pea (Pisum sativum L.) were mixed and processed to produce a MBPC, which was used to make a sausage analogue. The protein, moisture, and carbohydrate content were significantly (p<0.05) different among the samples. A significant (p<0.05) improvement was observed in textural properties (hardness, gumminess, and chewiness), cooking loss, frying loss, and emulsion stability of the sausage analogue. This study suggested the possibility of attaining high-quality sausage analogues and partial sausage analogues using MBPC, which could serve as a potential ingredient in meat analogues.

• The Journal of the Korea Contents Association
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• v.12 no.8
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• pp.105-113
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• 2012

With the help of information technology, the web 2.0 gives people the environment where they share informations and a means of expressing ideas. The power of web affects interactive storytelling for Alternate Reality Game (ARG). There are less theoretical approaches and practices about ARG in Korea and to understand ARG into a deeper sense shall contribute to the development of domestic culture and its contents. In order to realize this, first we will explore the general idea about ARG. Second, know its elements in Interactive storytelling and finally, analyze the examples.

• The Korean Journal of Applied Statistics
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• v.18 no.3
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• pp.597-606
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• 2005

The nonresponse in sample survey causes a problem when it comes time to analyze dataset in public-use files where the user has only complete-data methods available and has limited information about the reasons for nonresponse. Recently imputation for nonresponse is becoming a standard approach for handling nonresponse and various imputation methods have been devised . However, most imputation methods concern with continuous traits while many interesting features are measured by binary or ordered categorical scales in sample survey. In this note. an imputation method for ignorable nonresponse in binary or ordered categorical traits is considered.