• 한국정보통신학회논문지
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• 제24권7호
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• pp.904-913
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• 2020

데이터 볼륨과 복잡도가 빠르게 증가함에 따라 과학 빅데이터를 다루는 데이터 집적 과학은 네트워크를 통해 보다 효과적인 데이터 저장 및 분배를 위한 새로운 기술을 발견하는 것을 필요로 한다. 최근 네임드 데이터 네트워킹 커뮤니티와 데이터 집적 과학 커뮤니티는 함께 과학 실험 빅데이터의 분배 및 관리에 있어서 혁신적인 변화를 꾀하였다. 본 논문 에서는 기후과학 및 고에너지물리 데이터 등과 같은 과학 빅데이터를 위한 현존하는 엔디엔 테스트베드들에 대한 분석이 처음으로 이루어진다. 과학 빅데이터를 위한 엔디엔 테스트베드들을 현황, 엔디엔 기반 응용, 특징 측면에서 묘사하고 토의한다. 마지막으로 과학 빅데이터를 위한 엔디엔 테스트베드 네트워크를 확립함에 있어서, 함정에 빠질 수 있는 다양한 이슈들을 엔디엔 테스트베드들에 대한 묘사 그리고 특징들로 부터 도출하여, 분석 제시한다.

• 한국ITS학회 논문지
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• 제13권3호
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• pp.1-9
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• 2014

본 연구는 대형 이벤트가 발생하였을 때 신속하고 정확한 교통정책을 수립할 수 있도록 대형 이벤트 대응형 통합교통분석 시스템을 개발하는 데 목적이 있다. 교통분석 시스템 사례조사를 기초로 통합교통분석 시스템의 요건을 정의하고 개발방향을 수립하였다. 데이터 웨어하우스 (data warehouse) 구축을 위해 신속하고 정확한 교통정책 수립이 요구되는 대형 이벤트를 선정하고 데이터를 수집하였다. 수집된 대형 이벤트 데이터와 교통 데이터를 통합하여 데이터 웨어하우스와 주제별 데이터 마트 (data mart)를 구축하였다. 이용자가 적시에 의사결정을 할 수 있도록 비즈니스 인텔리전스(business intelligence) 시스템 화면을 설계하고 개발하였다.

• 한국지반공학회:학술대회논문집
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• 한국지반공학회 2003년도 봄 학술발표회 논문집
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• pp.503-508
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• 2003

In this study, we peformed ahead a field geological investigation, boring investigation for slope stability analysis in large scale slope failure area. But the geological stratum was not clearly grasped, because ground was very disturbed by large scale Granite intrusion. Furthermore, the existing test data was not pertinent to the large scale Granite intrusion site like here. Therefore, various kind of field test were performed to grasp clearly for geological stratum. And the results of back analysis, various kind tests used to slope stability analysis.

• Journal of Ship and Ocean Technology
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• 제5권4호
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• pp.44-50
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• 2001

Large container carriers are suffering from lack of knowledge on reliable correlation allowances between model tests and full-scale trials, especially at fully loaded condition, Careful full-scale sea trial with a full loading of containers both in holds and on decks was carried out to clarify it. Model test results were analyzed by different methods but with the same measuring data to figure out appropriated correlations factors for each analysis methods, Even if it is no doubt that model test technique is one of the most reliable tool to predict full scale powering performance, its assumptions and simplifications which have been applied on the course of data manipulation and analysis need a feedback from sea trial data for a fine tuning, so called correlation factor. It can be stated that the best correlation allowances at fully loaded condition for both 2-dimensional and 3-dimensional analysis methods are fecund through the careful sea trial results and relevant study on the large size container carriers.

• International Journal of Advanced Culture Technology
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• 제9권4호
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• pp.268-273
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• 2021

In this paper, we propose a sentiment analysis model that improves performance on small-scale data. A sentiment analysis model for small-scale data is proposed and verified through experiments. To this end, we propose Bagging-Bi-GRU, which combines Bi-GRU, which learns GRU, which is a variant of LSTM (Long Short-Term Memory) with excellent performance on sequential data, in both directions and the bagging technique, which is one of the ensembles learning methods. In order to verify the performance of the proposed model, it is applied to small-scale data and large-scale data. And by comparing and analyzing it with the existing machine learning algorithm, Bi-GRU, it shows that the performance of the proposed model is improved not only for small data but also for large data.

• Ocean and Polar Research
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• 제39권1호
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• pp.61-71
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• 2017

This study estimates the cost function through offshore fishery cost data and analyzed the economies of scale of Korea's offshore fishery. For the estimation of the cost function, translog cost function was used, and the analysis implemented the panel analysis of the panel data. Also, annual economies of scale of the offshore fishery and economies of scale of 14 offshore fisheries in 2015 were analyzed using translog cost function coefficient estimation. The analysis result of economies of scale of Korea's offshore fishery showed that with the exception of 2003, economies of scale exist in all periods of time. However, as it almost reaches the minimum efficient scale, it was revealed that further scale expansion will bring inefficiency. Thus, according to the analysis result, Korea's offshore fishery requires a scale reduction policy rather than scale expansion policy, and this seems to coincide with the current government's fishery reconstruction policy and its practice such as the fishing vessel buyback program. The analysis result of economies of scale of each offshore fishery in 2015 showed that economies of scale of each offshore fishery exists with the exception of five trawl fisheries such as large pair-trawl and large otter trawl and large purse seines. This strongly suggests that the five fisheries and Large Purse Seines with non performing economies of scale need urgent scale reduction and should be the first target for the government's fishery reconstruction policy.

• 유통과학연구
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• 제19권3호
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• pp.49-60
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• 2021

Purpose: This study aims to utilize geographic data to analyze how various retail formats of large-scale stores around the traditional market affect the performance of the traditional market in Seoul, Korea. Research design, data, and methodology: The two types of catchment areas were demarcated (circle of 1km radius and Thiessen polygon) for each traditional market, and the large-scale stores located within each catchment area were identified for 153 traditional markets in Seoul, Korea. Additionally, multiple regression analysis was utilized. Results: The results revealed that the influence on the performance of the traditional markets were different depending on the retail format of the large-scale stores. Large discount stores were found to have a negative effect on the sales and the visitors of traditional markets, whereas complex shopping malls and department stores had a positive effect on the traditional markets. Conclusions: As a result of the differences in the retail format such as product categories and leisure functions, the impact of some large-scale stores on the traditional market may have a greater agglomeration effect than the consumer churn effect. Therefore, it is suggested that in the regulation of these large-scale stores, the differences in retail format should be considered for the future.

• Journal of Communications and Networks
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• 제16권5호
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• pp.534-547
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• 2014

Large-scale failures resulting from natural disasters or intentional attacks are now causing serious concerns for communication network infrastructure, as the impact of large-scale network connection disruptions may cause significant costs for service providers and subscribers. In this paper, we propose a new framework for the analysis and prevention of network service disruptions in large-scale failure scenarios. We build dynamic deterministic and probabilistic models to capture the impact of regional failures as they evolve with time. A probabilistic failure model is proposed based on wave energy behaviour. Then, we develop a novel approach for preventive protection of the network in such probabilistic large-scale failure scenarios. We show that our method significantly improves uninterrupted delivery of data in the network and reduces service disruption times in large-scale regional failure scenarios.

• International Journal of Internet, Broadcasting and Communication
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• 제16권2호
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• pp.119-126
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• 2024

The volume of genomic data is constantly increasing in various modern industries and research fields. This growth presents new challenges and opportunities in terms of the quantity and diversity of genetic data. In this paper, we propose a distributed cloud system for integrating and managing large-scale gene databases. By introducing a distributed data storage and processing system based on the Hadoop Distributed File System (HDFS), various formats and sizes of genomic data can be efficiently integrated. Furthermore, by leveraging Spark on YARN, efficient management of distributed cloud computing tasks and optimal resource allocation are achieved. This establishes a foundation for the rapid processing and analysis of large-scale genomic data. Additionally, by utilizing BigQuery ML, machine learning models are developed to support genetic search and prediction, enabling researchers to more effectively utilize data. It is expected that this will contribute to driving innovative advancements in genetic research and applications.

• 한국전산구조공학회논문집
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• 제12권3호
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• pp.385-396
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• 1999

최근 공학분야에서 다루어지고 있는 문제의 규모가 대형화하고 있으며 이러한 대형구조물의 구조설계는 부재의 강도설계 및 절점의 변위조절을 위하여 많은 수의 구조해석을 요구한다. 한 대의 개인용 컴퓨터에 의한 대형구조물의 구조해석은 대용량의 기억장치와 많은 계산 시간이 요구되므로 반복적 해석이 필요한 대형구조물의 설계에 효율적으로 이용되기 어려운 실정이다. 따라서, 본 논문에서는 이러한 문제에 대한 대안으로 다수의 개인용 컴퓨터들을 네트워크로 연결하여 고성능 병렬연산시스템을 구성하고 이에 적합한 두 가지 형태의 분산구조방정식해법들을 반복법인 PCG 알고리즘을 이용하여 개발하였다. 대형구조물을 위한 분산구조해석법은 구조해석 과정에 요구되는 각 컴퓨터 상호 간의 통신회수와 통신량을 최소화할 수 있도록 개발되었다. 분산구조해석법의 성능은 대규모 3차원 트러스 구조물 및 144층 가새 튜브구조물의 구조해석에 적용하여 분석하였다.