• 융합보안논문지
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• 제16권7호
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• pp.21-29
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• 2016

현재 우리사회는 네트워크를 통하여 실시간으로 교류되는 다양한 정보 환경에 노출되어 있다. 특히 정부의 의료정책은 대국민의료서비스 질을 향상시키기 위해 원격진료의 시행을 서두르고 있다. 이러한 원격진료의 시행은 향후 지역에 상관없이 맞춤형 환자 진료를 위한 빅 데이터 기반의 진료 정보 구축도 함께 요구하고 있다. 본 논문은 빅 데이터 기반의 권역별 의료클러스터 구축과 이에 대한 서비스 가용성을 해치는 공격이 발생할 경우 해당 공격을 탐지하고 적절한 대응이 가능한 방어 및 보안 협력모델을 제안하고 있다. 이를 위하여 동일 병원정보시스템으로 전국에 고루 분포된 지방의료원을 권역별 가상 의료클러스터 본부로 하는 네트워크 구성을 제안하였다. 아울러 의료클러스터에 발생할 수 있는 IP Spoofing 공격과 이에 따른 DDoS 공격에 실시간으로 대응 가능한 상호협력 보안 모델을 설계하여 단일 체계, 단일 보안정책이 가지는 한계성도 극복할 수 있도록 하였다.

• 보건행정학회지
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• 제30권2호
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• pp.199-210
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• 2020

Background: Based on the importance of ceasing smoking programs to control the regional disparity of smoking behavior in Korea, this study aims to reveal the variation of smoke rate and determinants of it for 229 provinces. An evaluation of the relative efficiency of the cease smoking program under the consideration of regional characteristics was followed. Methods: The main sources of data are the Korean Statistical Information Service and a national survey on the expenditure of public health centers. Multivariate regression is performed to figure the determinants of regional variation of smoking rate. Based on the result of the regression model, clustering analysis was conducted to group 229 regions by their characteristics. Three clusters were generated. Using data envelopment analysis (DEA), relative efficiency scores are calculated. Results from the pooled model which put 229 provinces in one model to score relative efficiency were compared with the cluster-separated model of each cluster. Results: First, the maximum variation of the smoking rate was 16.9%p. Second, sex ration, the proportion of the elder, and high risk drinking alcohol behavior have a significant role in the regional variation of smoking. Third, the population and proportion of the elder are the main variables for clustering. Fourth, dissimilarity on the results of relative efficiency was found between the pooled model and cluster-separated model, especially for cluster 2. Conclusion: This study figured regional variation of smoking rate and its determinants on the regional level. Unconformity of the DEA results between different models implies the issues on regional features when the regional evaluation performed especially on the programs of public health centers.

• 산업경영시스템학회지
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• 제40권4호
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• pp.246-252
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• 2017

In the defense acquisition, a company's goal is to maximize profits, and the government's goal is to allocate budgets efficiently. Each year, the government estimates the ratio of indirect cost sector to defense companies, and estimates the ratio to be applied when calculating cost of the defense articles next year. The defense industry environment is changing rapidly, due to the increasing trend of defense acquisition budgets, the advancement of weapon systems, the effects of the 4th industrial revolution, and so on. As a result, the cost structure of defense companies is being diversifying. The purpose of this study is to find an alternative that can enhance the rationality of the current methodology for estimating the ratio of indirect cost sector of defense companies. To do this, we conducted data analysis using the R language on the cost data of defense companies over the past six years in the Defense Integrated Cost System. First, cluster analysis was conducted on the cost characteristics of defense companies. Then, we conducted a regression analysis of the relationship between direct and indirect costs for each cluster to see how much it reflects the cost structure of defense companies in direct labor cost-based indirect cost rate estimates. Lastly a new ratio prediction model based on regularized regression analysis was developed, applied to each cluster, and analyzed to compare performance with existing prediction models. According to the results of the study, it is necessary to estimate the indirect cost ratio based on the cost character group of defense companies, and the direct labor cost based indirect cost ratio estimation partially reflects the cost structure of defense companies. In addition, the current indirect cost ratio prediction method has a larger error than the new model.

• 천문학회보
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• 제37권2호
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• pp.147.1-147.1
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• 2012

We present empirical fiducial sequences for horizontal-branch (HB) stars in a set of bright Galactic globular clusters previously observed in SDSS (An et al. 2008). Mean loci of HB stars are derived on color-magnitude diagrams with multiple color indices (u - g, g - r, g - i, and g - z ) in order to identify foreground/background objects as well as cluster RR Lyrae variables. We compare our fiducial sequences to the model predictions from Yonsei-Yale isochrones and test the accuracy of the stellar evolution models.

• Communications for Statistical Applications and Methods
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• 제3권2호
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• pp.161-168
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• 1996

Multistage hierarchical models and Bayesian inferences about finite population total estimations are considered. Here, Gibbs sampling approach that can be used to predict the marginal posterior means needed for Bayesian inferences is proposed.

• 천문학회보
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• 제40권1호
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• pp.41.1-41.1
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• 2015

Hierarchical galaxy formation models under LCDM cosmology predict that the most massive structures such as galaxy clusters (M > $10^{14}M_{\odot}$) appear late (z < 1) in the history of the universe through hierarchical clustering of small objects. Galaxy formation is also expected to be accelerated in overdense environments, with the star formation rate-density relation to be established at z ~ 2. In this talk, we present our search of massive structures of galaxies at 0.7 < z < 4, using the data from GOODS survey and our own imaging survey, Infrared Medium-deep Survey (IMS). From these studies, we find that there are excess of massive structures of galaxies at z > 2 in comparison to the Millennium simulation data. At 1 < z < 2, the number density of massive structures is consistent with the simulation data, but the star formation history is more or less identical between field and cluster. The star formation quenching process is dominated by internal process (stellar mass). The environmental effect becomes important only at z < 1, which contributes to create the well known star formation-density relation in the local universe. Our results suggest that galaxy formation models under LCDM cosmology may require further refinements to match the observation.

• 천문학회보
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• 제43권1호
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• pp.62.2-62.2
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• 2018

From the gaussian, near scale-invariant density perturbations observed in the CMB to the late time clustering of galaxies, CDM provides a minimal theoretical explanation for a variety of cosmological data. However accepting this explanation, requires that we include within our cosmic ontology a vacuum energy that is ~122 orders of magnitude lower than QM predictions, or alternatively a new scalar field (dark energy) that has negative pressure. Alternatively, modifications to Einstein's General Relativity have been proposed as a model for cosmic acceleration. Recently there have been many works attempting to test for modified gravity using the large scale clustering of galaxies, ISW, cluster abundance, RSD, 21cm observations, and weak lensing. In this work, we compare various modified gravity models using cosmic shear data from the Deep Lens Survey as well as data from CMB, SNe Ia, and BAO. We use the Bayesian Evidence to quantify the comparison robustly, which naturally penalizes complex models with weak data support. In this poster we present our methodology and preliminary constraints on f(R) gravity.

• Journal of Astronomy and Space Sciences
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• 제14권1호
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• pp.1-17
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• 1997

The results of a restricted numerical simulation for the color gradients within globular clusters have been presented. The standard luminosity function of M3 and Salperter's initial mass functions were used to generate model clusters as a fundamental population. Color gradients with the sample clusters for both King and power law cusp models of surface brightness distributions are discussed in the case of using the standard luminosity function. The dependence of color gradients on several parameters for the simulations with Salpter's initial mass functions, such as slope of initial mass functions, cluster ages, metallicities, concentration parameters of King model, and slopes of power law, are also discussed. No significant radial color gradients are shown to the sample clusters which are regenerated by a random number generation technique with various parameters in both of King and power law cusp models of surface brightness distributions. Dynamical mass segregation and stellar evolution of horizontal branch stars and blue stragglers should be included for the general case of model simulations to show the observed radial color gradients within globular clusters.

• Biomolecules & Therapeutics
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• 제24권3호
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• pp.207-243
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• 2016

Autism spectrum disorder (ASD) is a neurodevelopmental disorder characterized by social and communication impairments, as well as repetitive and restrictive behaviors. The phenotypic heterogeneity of ASD has made it overwhelmingly difficult to determine the exact etiology and pathophysiology underlying the core symptoms, which are often accompanied by comorbidities such as hyperactivity, seizures, and sensorimotor abnormalities. To our benefit, the advent of animal models has allowed us to assess and test diverse risk factors of ASD, both genetic and environmental, and measure their contribution to the manifestation of autistic symptoms. At a broader scale, rodent models have helped consolidate molecular pathways and unify the neurophysiological mechanisms underlying each one of the various etiologies. This approach will potentially enable the stratification of ASD into clinical, molecular, and neurophenotypic subgroups, further proving their translational utility. It is henceforth paramount to establish a common ground of mechanistic theories from complementing results in preclinical research. In this review, we cluster the ASD animal models into lesion and genetic models and further classify them based on the corresponding environmental, epigenetic and genetic factors. Finally, we summarize the symptoms and neuropathological highlights for each model and make critical comparisons that elucidate their clinical and neurobiological relevance.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2010년도 학술발표회
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• pp.268-272
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• 2010

The research presented here represents a collaborative effort with the SFWMD on developing scenarios for future climate for the SFWMD area. The project focuses on developing methodology for simulating precipitation representing both natural quasi-oscillatory modes of variability in these climate variables and also the secular trends projected by the IPCC scenarios that are publicly available. This study specifically provides the results for precipitation modeling. The starting point for the modeling was the work of Tebaldi et al that is considered one of the benchmarks for bias correction and model combination in this context. This model was extended in the framework of a Hierarchical Bayesian Model (HBM) to formally and simultaneously consider biases between the models and observations over the historical period and trends in the observations and models out to the end of the 21st century in line with the different ensemble model simulations from the IPCC scenarios. The low frequency variability is modeled using the previously developed Wavelet Autoregressive Model (WARM), with a correction to preserve the variance associated with the full series from the HBM projections. The assumption here is that there is no useful information in the IPCC models as to the change in the low frequency variability of the regional, seasonal precipitation. This assumption is based on a preliminary analysis of these models historical and future output. Thus, preserving the low frequency structure from the historical series into the future emerges as a pragmatic goal. We find that there are significant biases between the observations and the base case scenarios for precipitation. The biases vary across models, and are shrunk using posterior maximum likelihood to allow some models to depart from the central tendency while allowing others to cluster and reduce biases by averaging. The projected changes in the future precipitation are small compared to the bias between model base run and observations and also relative to the inter-annual and decadal variability in the precipitation.