• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2004년도 Proceedings of ISRS 2004
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• pp.57-59
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• 2004

This paper reports the observation of the interferometric synthetic aperture radar (InSAR) phase anomaly on a newly reclaimed mudflat, Hwaong, in west coast of Korea, detected by a series of Radarsat-l SAR data obtained mostly during 2003. The observed phase anomaly could be from subsidence of mud land caused by volumetric contraction of mud in dry season. This process must have been initiated from March 2002 when tidal water supply to this region was permanently blocked by the newly constructed embankment. The maximum subsidence rate measured from InSAR signal is about 3 cm per month. The local heterogeneity of the subsidence rate over the reclaimed mudflat may indicate various mud composition, surface-subsurface hydrological processes, or subsurface information of the mud and basement rock structure. In-situ measurement must follow to support this observation from space.

• 한국통계학회:학술대회논문집
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• 한국통계학회 2003년도 추계 학술발표회 논문집
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• pp.179-182
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• 2003

This study describes a new graphical method for assessing and characterizing effect modification by a matching covariate in matched case-control studies. This method to understand effect modification is based on a semiparametric model using a varying coefficient model. The method allows for nonparametric relationships between effect modification and other covariates, or can be useful in suggesting parametric models. This method can be applied to examining effect modification by any ordered categorical or continuous covariates for which cases have been matched with controls. The method applies to effect modification when causality might be reasonably assumed. An example from veterinary medicine is used to demonstrate our approach. The simulation results show that this method, when based on linear, quadratic and nonparametric effect modification, can be more powerful than both a parametric multiplicative model fit and a fully nonparametric generalized additive model fit.

• 한국전산유체공학회:학술대회논문집
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• 한국전산유체공학회 2003년도 추계 학술대회논문집
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• pp.63-68
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• 2003

The Grid[1] is a communication service that collaborates dispersed high performance computers so that those can be shared and worked together. So, the Grid enables a researcher to analyze a huge-sized problem which was impossible by using local resources. However, diverse communication speeds among computing resources and heterogeneity of computing resources can reduce parallel efficiency in the Grid, The present paper focuses on the development of an efficient load balancing algorithm suitable for the Grid. Proposed algorithm classifies the whole processors into several groups with relatively faster communication speeds. Computational domain is firstly partitioned to each group and then to the processor level considering the performance of each processor. Developed algorithm is validated in the homogeneous system by comparing the present result with the result of equally partitioned meshes and then applied to the heterogeneous system. Additionally, the present algorithm is expanded to be able to solve the decomposed domains and applied to some problems.

• International Journal of Computer Science & Network Security
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• 제22권2호
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• pp.193-198
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• 2022

Face Detection is one of the most important aspects of image processing, it considers a time-consuming problem in real-time applications such as surveillance systems, face recognition systems, attendance system and many. At present, commodity hardware is getting more and more heterogeneity in terms of architectures such as GPU and MIC co-processors. Utilizing those co-processors along with the existing traditional CPUs gives the algorithm a better chance to make use of both architectures to achieve faster implementations. This paper presents a hybrid implementation of the face detection based on the local binary pattern (LBP) algorithm that is deployed on both traditional CPU and MIC co-processor to enhance the speed of the LBP algorithm. The experimental results show that the proposed implementation achieved improvement in speed by 3X when compared to a single architecture individually.

• ETRI Journal
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• 제46권3호
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• pp.513-525
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• 2024

Deep neural networks trained on labeled medical data face major challenges owing to the economic costs of data acquisition through expensive medical imaging devices, expert labor for data annotation, and large datasets to achieve optimal model performance. The heterogeneity of diseases, such as Alzheimer's disease, further complicates deep learning because the test cases may substantially differ from the training data, possibly increasing the rate of false positives. We propose a reconstruction-based self-supervised anomaly detection model to overcome these challenges. It has a dual-subnetwork encoder that enhances feature encoding augmented by skip connections to the decoder for improving the gradient flow. The novel encoder captures local and global features to improve image reconstruction. In addition, we introduce an entropy-based image conversion method. Extensive evaluations show that the proposed model outperforms benchmark models in anomaly detection and classification using an encoder. The supervised and unsupervised models show improved performances when trained with data preprocessed using the proposed image conversion method.

• 대한두경부종양학회지
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• 제16권1호
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• pp.3-8
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• 2000

Background and Objectives: Adenoid cystic carcinoma of salivary glands is characterized by insidious growth over many years, local recurrences, and distant metastasis and classified to three distinct histologic subtypes: tubular, cribriform, and solid. The solid type is known to have the worst prognosis. However, histopathologic heterogeneity is observed in tumors from the same patient. We have attempted to elucidate the genotypic differences, characterized by polysomies of chromosome 17, in adenoid cystic carcinoma according to the phenotypic histopathologic heterogeneity. Materials and Methods: Fluorescence in situ hybridization was performed on formalin-fixed paraffin blocks from seven patients with head and neck adenoid cystic carcinoma, using the centromeric $\alpha$-satellite probe of chromosome 17 to detect nuclei exhibiting polysomy. The difference in polysomeric chromosome expression in cribriform, tubular, solid type and type I, II, III according to the Szanto classification was analyzed. Results: Polysomy of chromosome 17 was found in 15.28% of the cribriform type, in 15.68% of the tubular type, and in 18.87% of the solid type. The proportion of polysomy was statistically higher in the solid type than in the cribriform type(p<0.05), and the proportion of polysomy increased progressively from type 1 to type 3, but this trend was statistically insignificant(p>0.05). Conclusion: We suggest that there may be genetic variations in tumor from the same patient depending on the histopathologic heterogenetiy in adenoid cystic carcinomas.

• Journal of Microbiology and Biotechnology
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• 제28권9호
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• pp.1517-1526
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• 2018

Investigating bacterial diversity and its metabolic capabilities is crucial for interpreting the ecological patterns in a desert environment and assessing the presence of exploitable microbial resources. In this study, we evaluated the spatial heterogeneity of physicochemical parameters, soil bacterial diversity and metabolic adaptation at meter scale. Soil samples were collected from two quadrats of a desert (Thar Desert, India) with a hot, arid climate, very little rainfall and extreme temperatures. Analysis of physico-chemical parameters and subsequent variance analysis (p-values < 0.05) revealed that sulfate, potassium and magnesium ions were the most variable between the quadrats. Microbial diversity of the two quadrats was studied using Illumina bar-coded sequencing by targeting V3-V4 regions of 16S rDNA. As for the results, 702504 high-quality sequence reads, assigned to 173 operational taxonomic units (OTUs) at species level, were examined. The most abundant phyla in both quadrats were Actinobacteria (38.72%), Proteobacteria (32.94%), and Acidobacteria (9.24%). At genus level, Gaiella represented highest prevalence, followed by Streptomyces, Solirubrobacter, Aciditerrimonas, Geminicoccus, Geodermatophilus, Microvirga, and Rubrobacter. Between the quadrats, significant difference (p-values < 0.05) was found in the abundance of Aciditerrimonas, Geodermatophilus, Geminicoccus, Ilumatobacter, Marmoricola, Nakamurella, and Solirubrobacter. Metabolic functional mapping revealed diverse biological activities, and was significantly correlated with physicochemical parameters. The results revealed spatial variation of ions, microbial abundance and functional attributes in the studied quadrats, and patchy nature in local scale. Interestingly, abundance of the biotechnologically important phylum Actinobacteria, with large proposition of unclassified species in the desert, suggested that this arid environment is a promising site for bioprospection.

• 대한교통학회지
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• 제36권2호
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• pp.141-154
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• 2018

지속적으로 증가하는 국제선 항공수요에 대웅하기 위해 지방 광역권에도 새로운 공항 건설 및 기존 공항 확장 계획이 이루어지고 있다. 그러나 기존 항공수요예측은 우리나라 전체 항공수요 또는 주요 도시 간의 항공수요에 대해서 수행되어 왔으며, 지방의 고유 특성을 고려한 지역별 항공수요예측은 많이 이루어지지 않았다. 본 연구에서는 영남권 국제선 항공수요를 대상으로 하였고, 현실적으로 관측하기 어려운 지방 광역권의 고유 특성을 반영할 수 있는 패널 자료를 활용한 fixed-effects model을 최적 모형으로 제안하였다. 모형 검증결과를 살펴보면 패널 자료 분석은 시계열 특성을 가지는 몇 개의 거시 사회경제지표만을 사용한 모형에서 다루기 어려운 허구적 회귀와 미관찰 이질성을 효과적으로 처리하고 있음을 알 수 있다. 다양한 통계적 검증과 적합성 평가를 통해서 본 연구에서 제안한 fixed-effects model이 다른 계량경제 모형들에 비해서 영남권 국제선 수요예측에 있어서 우수함을 증명하였다.

• 한국정보통신학회:학술대회논문집
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• 한국정보통신학회 2017년도 춘계학술대회
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• pp.294-296
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• 2017

클라우드 컴퓨팅은 클라우드 노드에서 발생하는 모든 데이터를 클라우드 서버에 업로드하여, 서비스로서 사용자에게 제공하는 역할을 수행하는 컴퓨팅 기법이다. 이는 네트워크의 상황에 따라 실시간으로 서비스를 제공하기에는 어렵다. 그것은 로컬의 영역이 아니라 네트워크를 통하여 원격지로 정보를 전송하고, 클라우드에서 서비스를 제공하기 위해 추가적으로 다운로드를 해야 하기 때문이다. 이에 대한 대안으로 포그 컴퓨팅이 제안되었다. 본 논문에서는 클라우드, 포그 그리고 사용자 간의 효율적인 데이터 교환 기법을 제안하고자 한다. 제안된 포그는 사용자에게 서비스를 제공하고, 데이터를 수집하여 처리하도록 한다. 클라우드는 포그 간의 데이터 교환과 제어의 흐름을 담당하도록 한다. 우리는 이에 대한 데이터의 교환에 필요한 표준 방식을 제안한다. 이를 위한 적용은 BAN(Body Area Network)에서 발생하는 정보를 포그에서 처리 및 서비스를 하고, 클라우드는 중재 역할을 수행하는 시스템으로 한다. 이는 기기 또는 서비스 간에서 발생하는 데이터 이질성을 해결하고, 효율적인 데이터 이동을 제공할 수 있다.

• 정보처리학회논문지D
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• 제16D권5호
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• pp.701-714
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• 2009

서비스 기반의 전사적 데이터 통합은 기업 변화의 가속화에 따른 통합적인 데이터 관리가 필요하다. 기업 간 협업은 비즈니스 프로세스를 이용하여 분산된 데이터베이스들에 접근하여 이루어진다. 이러한 접근은 글로벌 쿼리 기반으로 수행되기 때문에 이기종간의 상호운용을 위해서 데이터 이질성, 스키마 이질성, 유효성 검증과 같은 문제가 선결되어야 한다. 따라서 협업은 동적이면서 신뢰성 있는 구조를 갖추어야 한다. 본 논문에서는 협업을 위한 XMDR-DSM(eXtended MetaData Registry-Data Service Mediator) 시스템을 제안한다. XMDR-DSM은 XMDR-DS와 XMDR-DQP, XMDR-DAI로 구성되어 글로벌 스키마와 로컬 스키마간의 매핑을 지원해주고, 데이터 접근 및 통합 서비스를 제공한다. 따라서 이기종 데이터베이스 상호간의 업무 지원이 가능하게 하고, 정보를 재활용 가능한 자산으로 확보할 수 있는 이점과 교환의 표준화를 제시할 수 있다. 그리고 워크플로우 기반의 비즈니스 프로세스 제공할 수 있으므로 일원화된 정보를 관리할 수 있게 된다. 따라서 정보 수명을 증대하고 비용절감을 할 수 있게 된다.