• KSII Transactions on Internet and Information Systems (TIIS)
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• 제17권8호
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• pp.2292-2313
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• 2023

With improving computing performance, various digital platforms are being developed to enable easily utilization of high-performance computing environments. EDISON 1.0 is an online simulation platform widely used in computational science and engineering education. As the research paradigm changes, the demand for developing the EDISON 1.0 platform centered on simulation into the EDISON 2.0 platform centered on data and artificial intelligence is growing. Herein, a data framework, a core module for data-centric research on EDISON 2.0 digital platform, is proposed. The proposed data framework provides the following three functions. First, it provides a data repository suitable for the data lifecycle to increase research reproducibility. Second, it provides a new data model that can integrate, manage, search, and utilize heterogeneous data to support a data-driven interdisciplinary convergence research environment. Finally, it provides an exploratory data analysis (EDA) service and data enrichment using an AI model, both developed to strengthen data reliability and maximize the efficiency and effectiveness of research endeavors. Using the EDISON 2.0 data framework, researchers can conduct interdisciplinary convergence research using heterogeneous data and easily perform data pre-processing through the web-based UI. Further, it presents the opportunity to leverage the derived data obtained through AI technology to gain insights and create new research topics.

• Smart Structures and Systems
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• 제32권1호
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• pp.49-59
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• 2023

A bridge transportation network supplies products from various source nodes to destination nodes through bridge structures in a target region. However, recent frequent earthquakes have caused damage to bridge structures, resulting in extreme direct damage to the target area as well as indirect damage to other lifeline structures. Therefore, in this study, a surrogate model-based comprehensive framework to estimate the seismic resilience of bridge transportation networks is proposed. For this purpose, total system travel time (TSTT) is introduced for accurate performance indicator of the bridge transportation network, and an artificial neural network (ANN)-based surrogate model is constructed to reduce traffic analysis time for high-dimensional TSTT computation. The proposed framework includes procedures for constructing an ANN-based surrogate model to accelerate network performance computation, as well as conventional procedures such as direct Monte Carlo simulation (MCS) calculation and bridge restoration calculation. To demonstrate the proposed framework, Pohang bridge transportation network is reconstructed based on geographic information system (GIS) data, and an ANN model is constructed with the damage states of the transportation network and TSTT using the representative earthquake epicenter in the target area. For obtaining the seismic resilience curve of the Pohang region, five epicenters are considered, with earthquake magnitudes 6.0 to 8.0, and the direct and indirect damages of the bridge transportation network are evaluated. Thus, it is concluded that the proposed surrogate model-based framework can efficiently evaluate the seismic resilience of a high-dimensional bridge transportation network, and also it can be used for decision-making to minimize damage.

• Journal of applied mathematics & informatics
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• 제41권5호
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• pp.1129-1143
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• 2023

Social media platforms have become an integral part of our daily lives, and they generate vast amounts of data that can be analyzed for various purposes. However, the quality of the data obtained from social media is often questionable due to factors such as noise, bias, and incompleteness. Enhancing data quality is crucial to ensure the reliability and validity of the results obtained from such data. This paper proposes an enhanced decision-making framework based on Business Decision Management Systems (BDMS) that addresses these challenges by incorporating a data quality enhancement component. The framework includes a backtracking method to improve plan failures and risk-taking abilities and a steep optimized strategy to enhance training plan and resource management, all of which contribute to improving the quality of the data. We examine the efficacy of the proposed framework through research data, which provides evidence of its ability to increase the level of effectiveness and performance by enhancing data quality. Additionally, we demonstrate the reliability of the proposed framework through simulation analysis, which includes true positive analysis, performance analysis, error analysis, and accuracy analysis. This research contributes to the field of business intelligence by providing a framework that addresses critical data quality challenges faced by organizations in decision-making environments.

• 한국건설관리학회논문집
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• 제12권1호
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• pp.141-152
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• 2011

도시재생사업의 시장 규모는 꾸준히 증가하고 있으며, 도시재생 사업에서 큰 비중을 차지하는 입체복합공간 개발사업 역시 증가하는 추세를 보이고 있다. 하지만 기존의 도시재생 관련 연구는 국내외 사례의 비교분석에 기반한 시사점 및 제도의 개선방안 도출이 주를 이루어왔으며, 사업성패여부와 관련 깊은 사업관리 분야의 연구, 특히 사업관리의 기초를 제공하는 성과관리에 대한 연구는 상대적으로 미비한 실정이다. 본 연구는 입체복합공간 개발사업의 성공적인 추진을 위해 공공발주자 관점의 프로그램 성과관리 체계를 구축하는데 목적을 두고 진행되었다. 이를 위해 기존 문헌분석, 전문가 인터뷰 등을 실시하였으며, 입체복합공간 개발사업의 시설물 유형별 성과지표 및 리스크 연계 성과지표를 도출하고, 프로그램 성과점수 통합방법을 제안하였다. 본 연구에서 제안한 성과관리 체계는 기본계획 수립단계에서부터 유지관리단계까지 전 생애주기를 고려하고 있으며, 시설물 유형별 성과를 실시간으로 파악 및 평가가 가능한 구조를 갖추고 있다. 또한 리스크 연계 성과관리 체계는 주요 리스크요인별 대응주체 및 대응방안을 제공함으로써 리스크가 높은 성과지표의 지속적인 추적 및 통제를 가능하게 하였다. 본 연구는 도시재생사업의 전 생애주기에 걸친 성과관리 기술 향상을 통해 해당 분야의 효율성 제고에 기여할 것으로 기대되며, 향후 데이터웨어하우스 기반의 웹기반 성과관리시스템의 기본구조로 활용될 것이다.

• ETRI Journal
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• 제39권2호
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• pp.202-212
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• 2017

With the advent of the Internet-of-Things paradigm, the amount of data production has grown exponentially and the user demand for responsive consumption of data has increased significantly. Herein, we present DART, a fast and lightweight stream processing framework for the IoT environment. Because the DART framework targets a geospatially distributed environment of heterogeneous devices, the framework provides (1) an end-user tool for device registration and application authoring, (2) automatic worker node monitoring and task allocations, and (3) runtime management of user applications with fault tolerance. To maximize performance, the DART framework adopts an actor model in which applications are segmented into microtasks and assigned to an actor following a single responsibility. To prove the feasibility of the proposed framework, we implemented the DART system. We also conducted experiments to show that the system can significantly reduce computing burdens and alleviate network load by utilizing the idle resources of intermediate edge devices.

• 한국방송∙미디어공학회:학술대회논문집
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• 한국방송공학회 2009년도 IWAIT
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• pp.400-403
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• 2009

EAP (Extensible Authentication Protocol) is often used as an authentication framework for two-party protocol which supports multiple authentication algorithms known as "EAP method". And PKMv2 in 802.16e networks use EAP as an authentication protocol. However, this framework is not efficient when the EAP peer executing handover. The reason is that the EAP peer and EAP server should re-run EAP method each time so that they authenticate each other for secure handover. This makes some delays, so faster re-authentication method is needed. In this paper, we propose a new design of the PKMv2 framework which provides fast re-authentication. This new framework and usage of the keys which used as a short-term credential bring better performance during handover process.

• International Journal of Internet, Broadcasting and Communication
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• 제15권2호
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• pp.22-30
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• 2023

The portable mobile devices with high performance and high speed 5G network activate and explode the demands for ubiquitous information services that remove the limitations of time for the communication and places to request for the information. NN (Nearest Neighbor) search is one of the most important types of queries to be processed efficiently in the information services. Various indexes have been proposed to support efficient NN search in the wireless broadcast system. The indexes adopting Hilbert curve, grid partition or Voronoi diagram enable the clients to search for NN quickly in the wireless broadcast channel. It is necessary that an efficient means to evaluate the performances of various indexes. In this paper, we propose an open framework that can adopt a variety of indexing schemes and evaluate and compare the performances of them. The proposed framework is organized with open and flexible structure that can adopt hybrid indexing schemes extensible to Voronoi diagram as well as simple indexing schemes. With the implemented framework, we demonstrate the efficiency and scalability and flexibility of the proposed framework by evaluating various indexing schemes for NN query.

• Asia pacific journal of information systems
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• 제21권2호
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• pp.19-42
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• 2011

This paper proposes a new framework to predict decision performance by investigating the cognitive fit of decision makers. We assume that every decision maker has two kinds of schema: emotional and rational. Cognitive fit is believed to have a close relationship with the two schemata and decision performance. In the literature on decision performance there is few studies investigating the relationship between the two schemata and cognitive fit. Therefore, our research purposes are twofold: (1) to provide a theoretical basis for the proposed framework describing the causal relationships among the two schemata, cognitive fit. and decision performance, and (2) to empirically prove its validity in the application to an Internet shopping environment. Based on the questionnaires from 104 respondents, we used a second order, confirmatory factor analysis (CFA) model to extract valid constructs, and a structural equation model (SEM) to calculate path coefficients and prove the statistical validity of our proposed research model. The experimental results supported our research model.

• 한국산학기술학회논문지
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• 제13권1호
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• pp.348-354
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• 2012

본 논문은 반도체 사업의 하나인 SoC에서 소프트웨어의 특성을 바탕으로 정량적인 소프트웨어 개발 능력을 측정하고 분석하기 위한 프레임워크를 제시한다. 본 논문에서는 이론적 모델(능력 피라미드) 뿐만아니라 SoC 임베디드 소프트웨어의 특성에 기반을 둔 측정 모델을 제안한다. 정량적인 소프트웨어 개발 능력 측정은 단지 지표를 수집하는 것만이 아니라 수집된 지표의 품질, 비용, 납기(QCD)를 분석하는데, 외부적으로는 프로그래머가 고객의 요구를 만족하는 소프트웨어를 개발할 수 있게 해주고, 내부적으로는 가시적인 생산성의 증가로 좀 더 효율적인 소프트웨어개발이 가능하게 해준다. 제안된 프레임워크를 사용하여, 논문에서는 정량적으로 임베디드 소프트웨어 개발 능력을 측정한다.

• 한국정보과학회논문지:컴퓨팅의 실제 및 레터
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• 제7권2호
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• pp.109-120
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• 2001

본 논문에서는 최적의 성능을 갖는 병렬프로그램 개발을 위한 도구로 이식성, 확장성, 효율성을 고려한 성능가시화 프레임워크의 설계 및 구현을 제시한다. 본 프레임워크는 독립적으로 개발 가능한 인스트루멘테이션 층, 인터페이스 층 그리고 가시화 층으로 이루어진 계층구조를 갖도록 설계되었다. 인스트루멘테이션 층은 사건(event) 포획을 위한 라이브러리인 ECL(Event Capture Library)로 구성되며, 인터페이스 층은 인스트루멘테이션 층과 가시화 층 간에 문제중심의 인터페이스를 제공하기 위해 개발된 EDL/JPAL(Event Description Language/Jave Problem-oriented trace Access Library)로 구성되었다. 또한 가시화 층은 뷰와 필터의 추가, 수정 및 custom 뷰 그룹의 구성이 용이하도록 plug and play 스타일로 설계되었다. 이렇게 구현된 성능 가시화 프레임워크는 독립된 도구로서 뿐만 아니라 프로그래밍, 디버깅 그리고 성능분석이 통합된 병렬프로그램 개발환경의 핵심도구로 사용될 수 있다.