• Journal of Information Technology Services
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• v.11 no.1
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• pp.155-171
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• 2012

With the continuous and outstanding development of information technology(IT), human being is coming to the new computing era which is called cloud computing. This era brings lots of huge benefits also at the same time release the resources of IT infrastructure and data boom for man. In the future no longer, most of IT service providers, enterprises, organizations and systems will adopt this new computing model. There are three main deployment models in cloud computing including public cloud, private cloud and hybrid cloud; each one also has its own cons and pros. While implementing any kind of cloud services, customers have to choose one of three above deployment models. Thus, our paper aims to represent a practical framework to help the adopter select which one will be the best suitable deployment model for their requirements by evaluating each model comprehensively. The framework is built by applying the analytic hierarchy process(AHP), namely benefit-cost-opportunity-risk(BCOR) model as a powerful and effective tool to serve the problem. The gained results hope not only to provide useful information for the readers but also to contribute valuable knowledge to this new area. In addition, it might support the practitioners' effective decision making process in case they meet the same issue and have a positive influence on the increase of right decision for the organization.

• KIPS Transactions on Computer and Communication Systems
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• v.4 no.5
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• pp.147-152
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• 2015

In general, there are two synchronization methods in parallel event-driven simulation, pessimistic approach and optimistic approach. In this paper, we propose a new approach, sporadic synchronization combining both for prediction-based parallel event-driven logic simulation. We claim this hybrid solution is pretty effective to minimize both checkpoint overhead and restart overhead, which are related problems with frequent false predictions for improving the performance of the prediction-based parallel event-driven logic simulation. The experiment has clearly shown the advantage of the proposed approach.

• 한국신재생에너지학회:학술대회논문집
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• 2006.06a
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• pp.333-338
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• 2006

본 연구는 현재 디젤발전기를 전원으로 사용하고 있는 도서지역에 신 재생에너지원의 조합으로 구성 된 발전시스템 보급의 경제성 분석을 검토해 보았다. 분석 대상 도서는 에너지 기술연구원의 풍속분포자료를 근거로 추자도, 거문도, 영산도를 선정하였으며, 풍속 그 외 일사량, 부하 자료는 부분적으로 실측된 자료를 바탕으로 재구성하고 시스템 구성 발전기 들의 비용 자료는 해외 시장의 자료를 이용하였다. 분석을 위한 도구로는 도서지 역 에서 단독으로 운영되는 신 재생복합 전력시스템의 최적 설계 및 운영을 위한 프로그램으로 해외의 여러 곳에서 활용 중인 Homer를 사용하였다. 분석 결과, 추자도와 거문도 지역에 신 재생복합 전력시스템을 도입 할 경우에는 도서지역의 신 재생복합 전력시스템 보급이 경제 적인 사업으로 나타났지만 신 재생에너지 원인 풍속이 낮은 값을 가지는 영산도의 경우에는 신 재생복합 전력시스템의 보급이 디젤발전기만 운영 할 경우보다 발전 단가를 높인다. 즉, 신 재생에너지 원이 조건에 맞을 경우에는 도서지역의 신 재생복합 전력시스템 보급이 경제 적인 사업이라고 볼 수 있지만 영산도의 경우와 같이 그렇지 않을 경우엔 기존의 시스템보다 발전단가를 높일 수 있으므로 도서지역에 대한 충분한 모니터링을 거친 후에 부지를 선정 해야 한다.

• Smart Structures and Systems
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• v.24 no.6
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• pp.733-744
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• 2019

Wind speed forecasting is critical for a variety of engineering tasks, such as wind energy harvesting, scheduling of a wind power system, and dynamic control of structures (e.g., wind turbine, bridge, and building). Wind speed, which has characteristics of random, nonlinear and uncertainty, is difficult to forecast. Nowadays, machine learning approaches (generalized regression neural network (GRNN), back propagation neural network (BPNN), and extreme learning machine (ELM)) are widely used for wind speed forecasting. In this study, two schemes are proposed to improve the forecasting performance of machine learning approaches. One is that optimization algorithms, i.e., cross validation (CV), genetic algorithm (GA), and particle swarm optimization (PSO), are used to automatically find the optimal model parameters. The other is that the combination of different machine learning methods is proposed by finite mixture (FM) method. Specifically, CV-GRNN, GA-BPNN, PSO-ELM belong to optimization algorithm-assisted machine learning approaches, and FM is a hybrid machine learning approach consisting of GRNN, BPNN, and ELM. The effectiveness of these machine learning methods in wind speed forecasting are fully investigated by one-year field monitoring data, and their performance is comprehensively compared.

• Earthquakes and Structures
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• v.17 no.4
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• pp.425-434
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• 2019

The most effective passive vibration control and seismic resistance options in a reinforced concrete (RC) high-rise building (HRB) are the base isolation and the tuned mass damper (TMD) system. Many options, which may be suitable or not for different soil types, with different types of bearing systems, like rubber isolator, friction pendulum isolator and tension/compression isolator, are investigated to resist the base straining actions under five different earthquakes. TMD resists the seismic response, as a control system, by reducing top displacement or the total movement of the structure. Base isolation and TMDs work under seismic load in a different way, so the combination between base isolation and TMDs will reduce the harmful effect of the earthquakes in an effective and systematic way. In this paper, a comprehensive study of the combination of TMDs with three different base-isolator types for three different soil types and under five different earthquakes is conducted. The seismic response results under five different earthquakes of the studied nine RC HRB models (depicted by the top displacement, base shear force and base bending moment) are compared to show the most suitable hybrid passive vibration control system for three different soil types.

• Journal of the Korean Solar Energy Society
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• v.30 no.2
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• pp.22-32
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• 2010

The world is facing environmental problem described as climate change and exhaustion of fossil fuel. In order to solve theses problems, importance of renewable energy is extremely growing. For stable energy supply, it is need to apply hybrid renewable energy systems in urban-scale, because some renewable energy system' outputs are greatly influenced by climatic condition. Especially, solar irradiation and wind velocity are influenced by urban geometric environment as well as climatic condition. Therefore it is necessary to evaluate the renewable energy potential according as urban form. This study aims to evaluate the potential of solar energy and wind energy in urban-scale and classify urban type according as characteristics of urban forms. The results of this study will be used to develop renewable energy system application guidelines for urban and energy planning.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.16 no.7
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• pp.630-638
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• 2004

Liquid desiccant dehumidification systems have the ability to provide efficient humidity and temperature control while saving the electrical energy requirement for air conditioning as compared to a conventional system. The dehumidifier and the regenerator form the heart of this system. The latent part of the cooling load is overcome using liquid desiccant. The model regenerator has been designed to study the absorption characteristic of the aqueous triethylene glycol (TEG) solution which is in the flow range from 20 to 50 LPM. Also, this system designed that was able to change the height of the regenerator and dehumidifier. Because the effect of performance have different result according the height. The effect of performance factors of the regenerator with inlet solution flow rate, air flow rate, solution concentration, solution temperature, brine temperature, air temperature and inlet air relative humidity have been analyzed. Data obtained are useful for design guidance and performance analysis of the hybrid air conditioning system.

• Nuclear Engineering and Technology
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• v.49 no.5
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• pp.996-1005
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• 2017

In this paper, nuclear data for cross sections of the $^{64}Zn(n,2n)^{63}Zn$, $^{64}Zn(n,3n)^{62}Zn$, $^{64}Zn(n,p)^{64}Cu$, $^{66}Zn(n,2n)^{65}Zn$, $^{66}Zn(n,p)^{66}Cu$, $^{67}Zn(n,p)^{67}Cu$, $^{68}Zn(n,p)^{68}Cu$, and $^{68}Zn(n,{\alpha})^{65}Ni$ reactions were studied for neutron energies up to 40 MeV. In the nuclear model calculations, TALYS 1.6, ALICE/ASH, and EMPIRE 3.2 codes were used. Furthermore, the nuclear data for the (n,2n) and (n,p) reaction channels were also calculated using various cross-section systematics at energies around 14-15 MeV. The code calculations were analyzed and obtained using the different level densities in the exciton model and the geometry-dependent hybrid model. The results obtained from the excitation function calculations are discussed and compared with literature experimental data, ENDF/B-VII.1, and the TENDL-2015 evaluated data.

• Korean Medical Education Review
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• v.23 no.3
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• pp.147-153
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• 2021

The coronavirus disease 2019 (COVID-19) pandemic made it necessary for medical schools to restructure their curriculum by switching from face-to-face instruction to various forms of flexible learning. Flexible learning is a student-centered approach to learning that has received interest in many educational sectors. It is a critical strategy for expanding access to higher education during the pandemic. As flexible learning includes online, blended, hybrid, and hyflex learning options, learners have the opportunity to select an instruction modality based on their needs and interests. The shift to flexible learning in medical education took place rapidly in response to the COVID-19 pandemic, and learners, instructors, and schools were not prepared for this instructional change. Through the lens of the technology acceptance model, human agency, and a social constructivist perspective, I examine students, instructors, and educational institutions' roles in successfully navigating the digital transformation era. The pandemic has also accelerated the use of advanced information and communication technologies, such as artificial intelligence and virtual reality, in learning. Through a review of the literature, this paper aimed to reflect on current flexible learning practices from the instructional design and educational technology perspective and explore emerging technologies that may be implemented in future medical education.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.7
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• pp.3447-3469
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• 2019

It is well-known that the cooperative communication and error control technology can improve the network performance, but most existing cooperative MAC protocols have not focused on how to cope with the contention process caused by cooperation and how to reduce the bad influence of channel packet error rate on the system performance. Inspired by this, this paper first modifies and improves the basic rules of the IEEE 802.11 Medium Access Control (MAC) protocol to optimize the contention among the multi-relay in a cooperative ARQ scheme. Secondly, a hybrid ARQ protocol with soft combining is adopted to make full use of the effective information in the error data packet and hence improve the ability of the receiver to decode the data packet correctly. The closed expressions of network performance including throughput and average packet transmission delay in a saturated network are then analyzed and derived by establishing a dedicated two-dimensional Markov model and solving its steady-state distribution. Finally, the performance evaluation and superiority of the proposed protocol are validated in different representative study cases through MATLAB simulations.