• Journal of the Korean Data and Information Science Society
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• 제18권4호
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• pp.1179-1189
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• 2007

In this paper, we estimate the proportion of individuals having health insurance in a given year for several small domains cross-classified by age, sex and other demographic characteristics using the data provided by the National Center for Health Statistics(NCHS). We employ Bayesian as well as frequentist methodology to obtain small domain estimates and the associated measures of precision. One of the new features of our study is that we utilize the survey weights along with the model to derive the small domain estimates.

• 농촌계획
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• 제10권2호
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• pp.43-49
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• 2004

According to the growing concerns of the public with efficiency and effects of regional policies, their assessment works have become an important issue. Up to now, several studies have been carried out on economic effects of policies using conventional cost/benefit analysis, while there have been few studies on assessment of amenity oriented policies. From the above consideration, this study tried to develop An Annual Expenditure Assessment Model (AEAM) for amenity-oriented policy-making in rural area. As a pre-work for model development, the hierarchical indices system for rural development and the classification system of expenditure were designed. Being based on high significant relationship between rural amenities and local government expenditure, a linear optimization model for maximization of regional amenity was constructed. Through a case study of Sunchang-gun, Chonbuk-province, the model applicability was ascertained.

• Coupled systems mechanics
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• 제7권5호
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• pp.509-524
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• 2018

A hierarchical multi-scale modeling strategy devoted to the study of a Bitumen-Bound Gravel (BBG) is presented in this paper. More precisely, the paper investigates the temperature-dependent linear viscoelastic of the material when submitted to low deformations levels and moderate number of cycles. In such a hierarchical approach, 3D digital Representative Elementary Volumes are built and the outcomes at a scale (here, the sub-mesoscale) are used as input data at the next higher scale (here, the mesoscale). The viscoelastic behavior of the bituminous phases at each scale is taken into account by means of a generalized Maxwell model: the bulk part of the behavior is separated from the deviatoric one and bulk and shear moduli are expanded into Prony series. Furthermore, the viscoelastic phases are considered to be thermorheologically simple: time and temperature are not independent. This behavior is reproduced by the Williams-Landel-Ferry law. By means of the FE simulations of stress relaxation tests, the parameters of the various features of this temperature-dependent viscoelastic behavior are identified.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제5권11호
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• pp.2068-2086
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• 2011

Based on the quincunx sub-sampling grid, the New Interleaved Hierarchical INTerpolation (NIHINT) method is recognized as a superior pyramid data structure for the lossless and progressive coding of natural images. In this paper, we propose a new image interpolation algorithm, Edge Adaptive Hierarchical INTerpolation (EAHINT), for a further reduction in the entropy of interpolation errors. We compute the local variance of the causal context to model the strength of a local edge around a target pixel and then apply three statistical decision rules to classify the local edge into a strong edge, a weak edge, or a medium edge. According to these local edge types, we apply an interpolation method to the target pixel using a one-directional interpolator for a strong edge, a multi-directional adaptive weighting interpolator for a medium edge, or a non-directional static weighting linear interpolator for a weak edge. Experimental results show that the proposed algorithm achieves a better compression bit rate than the NIHINT method for lossless image coding. It is shown that the compression bit rate is much better for images that are rich in directional edges and textures. Our algorithm also shows better rate-distortion performance and visual quality for progressive image transmission.

• 한국재난정보학회 논문집
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• 제17권3호
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• pp.512-520
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• 2021

연구목적: 연구의 목적은 도시특성과 개인특성이 개인의 건강수준에 미치는 영향관계를 분석하는 것이다. 연구방법:본 연구는 2016년 우리나라 지방자치단체에 대한 도시특성과 개인특성이 개인의 건강수준에 미치는 영향관계를 위계선형모형으로 분석하였다. 연구결과: 도시특성이 개인특성과 더불어 개인이 건강수준에 상당한 영향을 미치는 것으로 나타났다. 그 영향 정도가 매우 크나 일부 변수들은 통계적으로 유의하지 않아 향후 도시정책에 보다 세밀한 연구가 필요하다. 결론:도시특성은 개인의 건강수준에 영향을 미치지만 개별적인 도시정책의 변수에 대한 추가 연구가 필요하다.

• 한국사회복지학
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• 제61권3호
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• pp.103-127
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• 2009

사례관리의 수행요소가 지역거주 정신장애인의 삶의 질에 미치는 영향이 소비자 만족도에 의해 어떻게 매개되는지를 분석하였다. 분석대상은 지역사회정신보건서비스 기관 중 사례관리를 수행하는 18개 기관과, 이 기관의 서비스를 이용하는 381명의 정신장애인이다. 설문조사를 실시하였으며, 클라이언트 수준과 기관 수준의 자료를 동시에 고려하는 위계적 선형모형(HLM: Hierarchical Lineral Model)을 적용하여 검증하였다. 주요한 연구 결과는 실무자의 담당 사례량이 삶의 질에 직접적 영향을 주었다. 사례관리팀 접근은 소비자 만족도에 직접적 영향을 미친 반면, 소비자 만족도를 매개하여 삶의 질에 이르는 간접적 영향은 미미하였다. 적절한 사례량의 확보 및 사례관리자 확대, 팀접근의 유용성에 대한 실천적 함의를 제안하였다.

• Journal of Information Processing Systems
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• 제12권1호
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• pp.46-56
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• 2016

Dynamic textures are videos that exhibit a stationary property with respect to time (i.e., they have patterns that repeat themselves over a large number of frames). These patterns can easily be tracked by a linear dynamic system. In this paper, a model that identifies the underlying linear dynamic system using wavelet coefficients, rather than a raw sequence, is proposed. Content based threshold filtering based on Set Partitioning in a Hierarchical Tree (SPIHT) helps to get another representation of the same frames that only have low frequency components. The main idea of this paper is to apply SPIHT based threshold filtering on different bands of wavelet transform so as to have more significant information in fewer parameters for singular value decomposition (SVD). In this case, more flexibility is given for the component selection, as SVD is independently applied to the different bands of frames of a dynamic texture. To minimize the time complexity, the proposed model is implemented on a graphics processing unit (GPU). Test results show that the proposed dynamic system, along with a discrete wavelet and SPIHT, achieve a highly compact model with better visual quality, than the available LDS, Fourier descriptor model, and higher-order SVD (HOSVD).

• Asian-Australasian Journal of Animal Sciences
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• 제14권7호
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• pp.910-914
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• 2001

The teat number of a sow plays an important role for weaning pigs and has been utilized in selection of swine breeding stock. Various linear models have been employed for genetic analyses of teat number although the teat number can be considered as a count trait. Theoretically, Poisson error mixed models are more appropriate for count traits than Normal error mixed models. In this study, the two models were compared by analyzing data simulated with Poisson error. Considering the mean square errors and correlation coefficients between observed and fitted values, the Poisson generalized linear mixed model (PGLMM) fit the data better than the Normal error mixed model. Also these two models were applied to analyzing teat numbers in four breeds of swine (Landrace, Yorkshire, crossbred of Landrace and Yorkshire, crossbred of Landrace, Yorkshire, and Chinese indigenous Min pig) collected in China. However, when analyzed with the field data, the Normal error mixed model, on the contrary, fit better for all the breeds than the PGLMM. The results from both simulated and field data indicate that teat numbers of swine might not have variance equal to mean and thus not have a Poisson distribution.

• 전기전자학회논문지
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• 제16권2호
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• pp.95-101
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• 2012

위성 영상에서 건물형태를 발생하기위한 새로운 접근방식이 본 논문에서 제안되었다. 제안된 알고리즘은 낮은 수준의 선소들을 연결하고 유사한 개체들을 군집화하기 위해 선소 측정함수가 적용된 신경망이다. 제안된 신경망은 윤곽선 영상에서 추출된 윤곽선들을 군집화 목적으로 사용된다. 본 논문에서는 3차원 선소의 오류에 의한 군집화 결과의 비현실적 건물모델의 발생을 근원적으로 차단하기 위하여, 높이 정보를 이용한 계층적 군집화를 제안하였다. 제안된 새로운 거리척도의 신경망과 군집화를 통해 성공적인 건물모델의 재구성을 실험으로 보여주었다.

• Communications for Statistical Applications and Methods
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• 제29권3호
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• pp.373-391
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• 2022

The distribution of observations in most econometric studies with spatial heterogeneity is skewed. Usually, a single transformation of the data is used to approximate normality and to model the transformed data with a normal assumption. This assumption is however not always appropriate due to the fact that panel data often exhibit non-normal characteristics. In this work, the normality assumption is relaxed in spatial mixed models, allowing for spatial heterogeneity. An inference procedure based on Bayesian mixed modeling is carried out with a multivariate skew-elliptical distribution, which includes the skew-t, skew-normal, student-t, and normal distributions as special cases. The methodology is illustrated through a simulation study and according to the empirical literature, we fit our models to non-life insurance consumption observed between 1998 and 2002 across a spatial panel of 103 Italian provinces in order to determine its determinants. Analyzing the posterior distribution of some parameters and comparing various model comparison criteria indicate the proposed model to be superior to conventional ones.