• 한국빅데이터학회지
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• 제4권1호
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• pp.119-127
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• 2019

본 연구는 엔지니어링 분야에서 생성되는 대용량의 빅데이터를 효율적으로 저장, 관리, 분석하는 클라우드 기반 빅데이터 플랫폼을 제안하고자 한다. 클라우드 기반 빅데이터 플랫폼은 HPC 클라우드 환경, 엔지니어링 빅데이터 분석 플랫폼, 데이터 수집 및 처리 모듈, 인공지능 기반 분석 라이브러리, 응용서비스로 구성된다. 이를 통해 데이터 분석에 대한 전문지식이 없는 엔지니어링 전문가가 IoT 빅데이터를 수집 및 분석함으로써 산업적으로 활용이 가능하다. 마지막으로 응용서비스에서는 빅데이터 플랫폼 적용 사례를 제시하기 위해 하수처리플랜트 데이터를 이용하여 서비스를 구현하였다.

• International Journal of Internet, Broadcasting and Communication
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• 제12권4호
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• pp.218-225
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• 2020

The purpose of this paper is to establish an IoT-based big data platform that can check the space and form analysis in various play cultures of children. Therefore, to this end, in order to understand the healthy play culture of children, we are going to build a big data platform that allows IoT and smart devices to work together to collect data. Therefore, the goal of this study is to develop a big data platform linked to IoT first in order to collect data related to observation of children's mobile movements. Using the developed big data platform, children's play culture can be checked anywhere through observation and intuitive UI design, quick information can be automatically collected and real-time feedback, data collected through repeaters can be aggregated and analyzed, and systematic database can be utilized in the form of big data.

• Structural Monitoring and Maintenance
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• 제7권4호
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• pp.345-365
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• 2020

At present, many machine leaning and data mining methods are used for analyzing and predicting structural response characteristics. However, the platform that combines big data analysis methods with online and offline analysis modules has not been used in actual projects. This work is dedicated to developing a multifunctional Hadoop-Spark big data platform for bridges to monitor and evaluate the serviceability based on structural health monitoring system. It realizes rapid processing, analysis and storage of collected health monitoring data. The platform contains offline computing and online analysis modules, using Hadoop-Spark environment. Hadoop provides the overall framework and storage subsystem for big data platform, while Spark is used for online computing. Finally, the big data Hadoop-Spark platform computational performance is verified through several actual analysis tasks. Experiments show the Hadoop-Spark big data platform has good fault tolerance, scalability and online analysis performance. It can meet the daily analysis requirements of 5s/time for one bridge and 40s/time for 100 bridges.

• Journal of Multimedia Information System
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• 제4권4호
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• pp.271-278
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• 2017

There has been an influx of traders and researchers eager to gain a better understanding of the market due to the rapid growth of the FOREX market. Traders with varying degree of experience are also often inundated with information, analysis methods as well as trading rules when making a trading decision on buying/selling a currency exchange pair. Thus, this paper reviews the current computational tools and analysis methods used within the FOREX trading community and proposes the development of a web-based trading platform with e-learning features to support beginners. Novice traders could also benefit from the use of the proposed e-learning trading platform as it helps them gain valuable knowledge and navigate the FOREX market in real-time. Even experienced traders would find it useful as the platform could be used for actual trading and acts as a reference point to understand the reasoning behind the certain technical analysis implementation that are still unclear to them.

• Nuclear Engineering and Technology
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• 제56권3호
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• pp.1037-1051
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• 2024

This paper presents the construction results and design of the UNIST Reactor Innovation platform for small modular reactors as a versatile testbed for exploring innovative technologies. The platform uses simulant fluids to simulate the thermal-hydraulic behavior of a reference small modular reactor design, allowing for cost-effective design modifications. Scaling analysis results for single and two-phase natural circulation flows are outlined based on the three-level scaling methodology. The platform's capability to simulate natural circulation behavior was validated through performance calculations using the 1-D system thermal-hydraulic code-based calculation. The strategies for evaluating cutting-edge technologies, such as the integration of a solid oxide electrolysis cell for hydrogen production into a small modular reactor, are presented. To overcome experimental limitations, the hardware-in-the-loop technique is proposed as an alternative, enabling real-time simulation of physical phenomena that cannot be implemented within the experimental facility's hardware. Overall, the proposed versatile innovation platform is expected to provide valuable insights for advancing research in the field of small modular reactors and nuclear-based hydrogen production.

• International journal of advanced smart convergence
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• 제10권3호
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• pp.41-50
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• 2021

The purpose of this study is to analyze various energy platforms using data in the US and to suggest directions and implications. Some of the leading energy platforms are selected and analyzed based on the opening platform model. We focus on the case analysis of the US utility companies. In case of the horizontal open platform, Green Button sponsor's 'Connect My Data (CMD)' driven by the government invites the utility companies to jointly develop the sponsor's data solution. In case of the vertical open platform, the certification program 'Share My Data (SMD)' allows backward compatibility, because the technical improvement is minimal. The utility companies benchmark Amazon's three-sided market mediation and prefer platform and category exclusivity. For the former, they have data analytics companies like Enervee, Opower and for the latter, they have electronics manufactures and energy service providers (ESPs) like Distributed Energy Resources (DERs). Based on this US case study, we suggest the energy platforms to open their platform for renewable energy supply, energy conservation, high-efficiency products, and residential DER dissemination. To successfully implement the government's energy transition policy, the US platforms should be benchmarked as a business model. Especially, it is needed for them to coordinate a platform ecosystem. To ensure trust in the products and services offered on the marketplace platform, platform's certification program is helpful.

• 한국해양공학회지
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• 제30권2호
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• pp.84-90
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• 2016

In this study, a six degree-of-freedom motion analysis of a wind-wave hybrid platform equipped with numerous wave energy converters (WECs) was carried out. To examine the effect of the WECs on the platform, an analysis of one-way coupling was carried out, which only considered the power take-off (PTO) damping of the static WECs on the platform. The equation of motion of a floating platform with mooring lines in the time domain was established, and the responses of the one-way coupled platform were then compared with the case of a platform without any coupling effects from the WECs. The hydrodynamic coefficients and wave exciting forces were obtained from the 3D diffraction/radiation pre-processor code WAMIT based on the boundary element method. Then, an analysis of the dynamic responses of the floating platform with or without the WEC effect in the time domain was carried out. All of the dynamics of a floating platform with multiple wind turbines were obtained by coupling FAST and CHARM3D in the time domain, which was further extended to include additional coupled dynamics for multiple turbines. The analysis showed that the PTO damping effect on platform motions was negligible, but coupled effects between multiple WECs and the platform may differentiate the heave, roll, and pitch platform motions from the one without any effects induced by WECs.

• 산업경영시스템학회지
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• 제46권3호
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• pp.109-122
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• 2023

As platforms become primary decision making tools, platforms for decision have been introduced to improve quality of decision results. Because, decision platforms applied augmented decision-making process which uses experiences and feedback of users. This process creates a variety of alternatives tailored for users' abilities and characteristics. However, platform users choose alternatives before considering significant quality factors based on securing decision quality. In real world, platform managers use an algorithm that distorts appropriate alternatives for their commercial benefits. For improving quality of decision-making, preceding researches approach trying to increase rational decision -making ability based on experiences and feedback. In order to overcome bounded rationality, users interact with the machine to approach the optional situation. Differentiated from previous studies, our study focused more on characteristics of users while they use decision platforms. This study investigated the impact of quality factors on decision-making using platforms, the dimensions of systematic factors and user characteristics. Systematic factors such as platform reliability, data quality, and user characteristics such as user abilities and biases were selected, and measuring variables which trust, satisfaction, and loyalty of decision platforms were selected. Based on these quality factors, a structural equation research model was created. A survey was conducted with 391 participants using a 7-point Likert scale. The hypothesis that quality factors affect trust was proved to be valid through path analysis of the structural equation model. The key findings indicate that platform reliability, data quality, user abilities, and biases affect the trust, satisfaction and loyalty. Among the quality factors, group bias of users affects significantly trust of decision platforms. We suggest that quality factors of decision platform consist of experience-based and feedback-based decision-making with the platform's network effect. Through this study, the theories of decision-making are empirically tested and the academic scope of platform-based decision-making has been further developed.

• 한국전산구조공학회논문집
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• 제34권5호
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• pp.263-270
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• 2021

본 연구에서는 환경, 재료 물성 및 제작 등에서의 불확실성을 고려하여 130m급 고정식 해양구조물의 신뢰성 기반 최적설계를 수행하였다. 구조물의 구조건전성을 엄밀하게 반영하기 위해 작용 및 허용 응력의 비인 UC 값을 신뢰성 해석 및 신뢰성 기반 최적설계의 제약조건으로 고려하였다. 해양구조물의 제작비용을 저감하기 위해 자켓형 지지구조물의 중량을 최소화하였다. 불확실성의 통계적 특성은 문헌 등을 참고하여 관측되거나 측정된 데이터를 기반으로 정의하였다. 자켓형 해양구조물의 신뢰성 해석과 신뢰 기반 최적설계는 부재 수가 많아 계산 부담이 큼으로 문제의 차원을 축소하기 위해 응답의 중요성을 기준으로 설계변수를 선별할 수 있는 방법을 제안한다. 또한 효율적인 계산을 위해 신뢰성 기반 최적설계를 수행하기 전 결정론적 최적설계를 먼저 수행하였다. 마지막으로, 도출된 최적설계(안)을 기존 각 급 규정 기반 설계와 안전성 및 경제성 측면에서 비교 분석하였다.

• 한국IT서비스학회지
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• 제11권2호
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• pp.19-47
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• 2012

Contemporary smartphone competition is generally described as the battle between Apple's proprietary platform and Google's open platform. However, this competition is not limited within smartphone adoption itself. User's pre-adoption of one mobile platform via smartphone can be connected to the post-adoption of the same mobile platform based on the other smart devices (e.g. smart pad). In this study, we investigate whether user's preference to a certain platform is persistent over mobile ecology, from the pre-adoption of one smart device to the post-adoption of following devices. For this investigation, we adopt the dual-model as the ground theory, where post-adoption of IT product is explained by both dedication and constraint factors. The empirical testing first evidences that dual model works well as our research model for identifying the reasons of post-adoption. Next, we group our data into two parts in order to compare the switching behavior of iPhone users and Android phone users. iPhone users show much lower switching rate to Android based smart pads, while Android phone users show higher churn rate to iPad (49.3% : 96.3%). Especially, satisfaction showed much stronger effect than switching cost on the continuing intention of existing platform, when the analysis is given to the iPhone user's group. From this result, we can conjecture the relatively stronger loyalty of iPhone users. More managerial implications on the mobile platform strategy are driven.