• Structural Engineering and Mechanics
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• 제64권4호
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• pp.473-485
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• 2017

An isolated building, composed of superstructure and isolation system which have very different damping properties, is typically non-classical damping system. This results in inapplicability of traditional response spectrum method for isolated buildings. A multidimensional response spectrum method based on complex mode superposition is herein introduced, which properly takes into account the non-classical damping feature in the structure and a new method is developed to estimate velocity spectra from the commonly used displacement or pseudo-acceleration spectra based on random vibration theory. The error of forced decoupling method, an approximated approach, is discussed in the viewpoint of energy transfer. From the base-isolated benchmark model, as a numerical example, application of the procedure is illustrated companying with comparison study of time-history method, forced decoupling method and the proposed method. The results show that the proposed method is valid, while forced decoupling approach can't reflect the characteristics of isolated buildings and may lead to insecurity of structures.

• 한국지능시스템학회논문지
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• 제18권4호
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• pp.555-561
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• 2008

GA 기반의 4족 보행로봇의 걸음새의 속도와 안정성을 최적화하는 걸음새의 자동 생성 방법을 구현한다. 기존에 사용된 걸음새 파라미터 집합에서 중요 파라미터의 영향을 분석하였고, 이를 통해 효율적인 탐색 방향을 설정하였다. 또한 속도 위주의 기존 연구와는 달리 반 정확도가 수반된 결과를 얻도록 하였다. 제안된 기법의 검증을 위하여 SONY Aibo 4족 보행 로봇에 대해서 ODE 기반의 물리적 특성을 포함한 정교한 시뮬레이션이 가능한 Webots 을 이용하여 실험을 수행하였고, 속도와 안정성 면에서 향상된 결과를 얻었다.

• 정보처리학회논문지D
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• 제15D권1호
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• pp.31-40
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• 2008

유사 시퀀스 매칭에서는 고차원인 시퀀스를 저차원의 점으로 변환하기 위하여 저차원 변환을 사용한다. 그런데, 이러한 저차원 변환은 시계열 데이터의 종류에 따라 인덱싱 성능에 있어서 큰 차이를 나타낸다. 즉, 어떤 저차원 변환을 선택하느냐가 유사 시퀀스 매칭의 인덱싱 성능에 큰 영향을 주게 된다. 이 문제를 해결하기 위하여, 본 논문에서는 하나의 인덱스에서 두 개 이상의 저차원 변환을 통합하여 사용하는 하이브리드 접근법을 제안한다. 먼저, 하나의 시퀀스에 두 개 이상의 저차원 변환을 적용하는 하이브리드 저차원 변환의 개념을 제안하고, 변환된 시퀀스간의 거리를 계산하는 하이브리드 거리를 정의한다. 다음으로, 이러한 하이브리드 접근법 사용하면 유사 시퀀스 매칭을 정확하게 수행할 수 있음을 정형적으로 증명한다. 또한, 제안한 하이브리드 접근법을 사용하는 인덱스 구성 및 유사 시퀀스 매칭 알고리즘을 제시한다. 다양한 시계열 데이터에 대한 실험 결과, 제안한 하이브리드 접근법은 단일 저차원 변환을 사용하는 경우에 비해서 우수한 성능을 보이는 것으로 나타났다. 이 같은 결과를 볼 때, 제안한 하이브리드 접근법은 다양한 특성을 지닌 다양한 시계열 데이터에 두루 적용될 수 있는 우수한 방법이라 사료된다.

• Nuclear Engineering and Technology
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• 제53권10호
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• pp.3182-3195
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• 2021

The implementation and validation of multi-dimensional (multi-D) features in thermal-hydraulic system codes aims to extend the application of these codes towards multi-scale simulations. The main goal is the simulation of large-scale three-dimensional effects inside large volumes such as piping or vessel. This novel approach becomes especially relevant during the simulation of accidents with strongly asymmetric flow conditions entailing density gradients. Under such conditions, coolant mixing is a key phenomenon on the eventual variation of the coolant temperature and/or boron concentration at the core inlet and on the extent of a local re-criticality based on the reactivity feedback effects. This approach presents several advantages compared to CFD calculations, mainly concerning the model size and computational efforts. However, the range of applicability and accuracy of the newly implemented physical models at this point is still limited and needs to be further extended. This paper aims at contributing to the validation of the multi-D features of the system code ATHLET based on the simulation of the Tests 1.1 and 2.1, conducted at the test facility ROCOM. Overall, the multi-D features of ATHLET predict reasonably well the evolution from both experiments, despite an observed overprediction of coolant mixing at the vessel during both experiments.

• 한국정보시스템학회지:정보시스템연구
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• 제31권1호
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• pp.115-146
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• 2022

Purpose The purpose of this study is to find meaningful insights using regression analysis to resolve the digital divide between generations. In the analysis process of this study, social network analysis was applied to approach it with a perspective differentiated from the existing statistical techniques. Design/methodology/approach This study used a social network analysis methodology that transforms and analyzes government-led survey data into relational data. First, the cross-sectional data were converted into relational data, and a continuous core-periphery model and multidimensional scaling method were applied. Afterwards, the relationship between various factors affecting the digital divide and the difference in influence were analyzed by generation. Findings According to the network analysis results, it can be seen that all generations commonly use 'information and news search' and 'living information service'. However, it can be seen that the centrally used services of each generation are clearly different from each other, and the degree of linkage between the services is also clearly different. In addition, it can be seen that the relationship between factors influencing the digital divide by generation is also different.

• 한국콘텐츠학회논문지
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• 제10권8호
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• pp.138-146
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• 2010

IPTV에 대한 관심이 높아짐에 따라 수많은 콘텐츠를 사용자가 쉽고 빠르게 찾아 소비할 수 있는 인터페이스에 대한 필요성 뿐 아니라 개인의 취향이 반영되는 메뉴 구조에 대한 요구가 대두되고 있다. 기존의 IPTV 브라우저는 콘텐츠 종류에 따라 메뉴 검색 기준이 다르게 제시되어 직관적 사용이 어려웠으며, 사용자의 특성을 고려하지 않은 인터페이스를 제공함으로써 사용자와 콘텐츠의 상호작용에 한계가 있었다. 이에 본 논문에서는 IPTV 내에서 사용자 요구에 맞춰 콘텐츠 종류에 상관없이 적용 가능한 다차원 멀티미디어 콘텐츠 브라우저를 제안한다. 이를 위해 메뉴 분류 방식을 동일하게 적용하고 다차원 기준을 단순시각화하여 직관적 사용이 가능하도록 함으로써 사용자가 콘텐츠에 대한 자세한 정보 없이도 다차원 검색만으로 원하는 콘텐츠 소비가 가능하도록 하고자 한다.

• 보건교육건강증진학회지
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• 제24권1호
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• pp.93-108
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• 2007

Background: School is a primary health education setting for children and the continuous support should be provided to renew school health education curriculum correspondent to socio-cultural changes in Korean society. Objectives: This study was conducted to identify the principals' and teachers' needs of health education topics for their students and to analyze their conceptual map for health education curriculum in Korean elementary school. Methods: The sample size of the first survey was 179 and that of the second survey was 691 of elementary school principals and teachers from stratified sampling over Korea. The self-administered mailing survey was conducted to o identify the factor structure of the health education topics and to analyze the conceptual properties with exploratory factor analysis and multidimensional scaling analysis in SPSS 12.0. Results: A total of 21 health education topics were collected from the first survey and 31 topics were, comprehensively, generated for the second survey. The five factors were determined: 'life health promotion behavior,' 'drug control and mental health,' 'bulling and aggression prevention,' 'safety perception and injury prevention,' and 'sex education and sexual harassment.' The educational need scores were the highest in 'safety perception and injury prevention.' The two-dimensional cooperates were generated for the 31 health education topics and the two dimensional properties which divided the conceptual space were 'health-safety' for one and 'public/environmental-individual/personal' for the other. Conclusions: Health education curriculum and textbook should be developed considering teachers' needs and conditions for health education in school fields. The field-based health education programs or textbook would make more possible problem-solving health education for children in real school fields.

• International Journal of Computer Science & Network Security
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• 제23권12호
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• pp.101-106
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• 2023

Chronic illnesses are among the most common serious problems affecting human health. Early diagnosis of chronic diseases can assist to avoid or mitigate their consequences, potentially decreasing mortality rates. Using machine learning algorithms to identify risk factors is an exciting strategy. The issue with existing feature selection approaches is that each method provides a distinct set of properties that affect model correctness, and present methods cannot perform well on huge multidimensional datasets. We would like to introduce a novel model that contains a feature selection approach that selects optimal characteristics from big multidimensional data sets to provide reliable predictions of chronic illnesses without sacrificing data uniqueness.[1] To ensure the success of our proposed model, we employed balanced classes by employing hybrid balanced class sampling methods on the original dataset, as well as methods for data pre-processing and data transformation, to provide credible data for the training model. We ran and assessed our model on datasets with binary and multivalued classifications. We have used multiple datasets (Parkinson, arrythmia, breast cancer, kidney, diabetes). Suitable features are selected by using the Hybrid feature model consists of Lassocv, decision tree, random forest, gradient boosting,Adaboost, stochastic gradient descent and done voting of attributes which are common output from these methods.Accuracy of original dataset before applying framework is recorded and evaluated against reduced data set of attributes accuracy. The results are shown separately to provide comparisons. Based on the result analysis, we can conclude that our proposed model produced the highest accuracy on multi valued class datasets than on binary class attributes.[1]

• 대한지역사회영양학회지
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• 제29권1호
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• pp.34-50
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• 2024

Objectives: Transformation through a sustainable food system to provide healthy diets is essential for enhancing both human and planetary health. This study aimed to explain about sustainable diets and illustrate appropriate measurement of adherence to sustainable diets using a pre-existing index. Methods: For literature review, we used PubMed and Google Scholar databases by combining the search terms "development," "validation," "sustainable diet," "sustainable diet index," "planetary healthy diet," "EAT-Lancet diet," and "EAT-Lancet reference diet." For data presentation, we used data from National Health and Nutrition Examination Survey, 2017-2018, among adults aged 20 years and older (n = 3,920). Sustainable Diet Index-US (SDI-US), comprising four sub-indices corresponding to four dimensions of sustainable diets (nutritional quality, environmental impacts, affordability, and sociocultural practices), was calculated using data from 24-hour dietary recall interview, food expenditures, and food choices. A higher SDI-US score indicated greater adherence to sustainable diets (range: 4-20). This study also presented SDI-US scores according to the sociodemographic status. All analyses accounted for a complex survey design. Results: Of 148 papers, 16 were reviewed. Adherence to sustainable diets fell into 3 categories: EAT-Lancet reference diet-based (n = 8), Food and Agriculture Organization (FAO) definition-based (n = 4), and no specific guidelines but including the sustainability concept (n = 4). Importantly, FAO definition emphasizes on equal importance of four dimensions of diet (nutrition and health, economic, social and cultural, and environmental). The mean SDI-US score was 13 out of 20 points, and was higher in older, female, and highly educated adults than in their counterparts. Conclusions: This study highlighted that sustainable diets should be assessed using a multidimensional approach because of their complex nature. Currently, SDI can be a good option for operationalizing multidimensional sustainable diets. It is necessary to develop a Korean version of SDI through additional data collection, including environmental impact of food, food price, food budget, and use of ready-made products.

• Asian Journal of Innovation and Policy
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• 제1권2호
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• pp.200-218
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• 2012

Estimating the economic life of a technology is the first important prerequisite step in the feasibility analysis of technology-based business. Many empirical studies have concentrated on patents data to estimate the time period for a technology. However, it is recommended to estimate it along with qualitative considerations of future technological and market conditions. In this regard, little is known about how approaches are applied. This paper aims to establish a structural framework of estimating the lifetime of a technology by integrating the outputs of an analysis of the determinants in each transition of a product life cycle. We describe an illustrative case about a light emitting diode (LED) backlight unit (BLU) technology for the liquid crystal display (LCD) TV. The framework allows valuators and experts to estimate a technology lifetime by using multidimensional factors.