• 대기
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• 제23권3호
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• pp.321-329
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• 2013

This study examines the effect of aerosols on the vertical invigoration of continental stratiform clouds, using a dataset of Atmospheric Radiation Measurement (ARM) Intensive Operational Period (IOP, March 2000) at the Southern Great Plains (SGP) site. To provide further support to our observation-based findings, the weather research and forecasting (WRF) sensitivity simulations with changing cloud condensation nuclei (CCN) concentrations have been carried out for the golden episode over SGP. First, cross correlation between observed aerosol scattering coefficient and cloud liquid water path (LWP) with a 160-minutes lag is the highest of r = 0.83 for the selected episode, which may be attributable to cloud vertical invigoration induced by an increase in aerosol loading. Modeled cloud fractions in a control run are well matched with the observation in the perspective of cloud morphology and lasting period. It is also found through a simple sensitivity with a change in CCN that aerosol invigoration (AIV) effect on stratiform cloud organization is attributable to a change in the cloud microphysics as well as dynamics such as the corresponding modification of cloud number concentrations, drop size, and latent heating rate, etc. This study suggests a possible cloud vertical invigoration even in the continental stratiform clouds due to aerosol enhancement in spite of a limited analysis based on a few observed continental cloud cases.

• Asia pacific journal of information systems
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• 제22권3호
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• pp.99-124
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• 2012

Our society has long been talking about necessity for innovation. Since companies in particular need to carry out business innovation in their overall processes, they have attempted to apply many innovation factors on sites and become to pay more attention to their innovation. In order to achieve this goal, companies has applied various information technologies (IT) on sites as a means of innovation, and consequently IT have been greatly developed. It is natural for the field of IT to have faced another revolution which is called cloud computing, which is expected to result in innovative changes in software application via the Internet, data storing, the use of devices, and their operations. As a vehicle of innovation, cloud computing is expected to lead the changes and advancement of our society and the business world. Although many scholars have researched on a variety of topics regarding the innovation via IT, few studies have dealt with the issue of could computing as IT. Thus, the purpose of this paper is to set the variables of innovation attributes based on the previous articles as the characteristic variables and clarify how these variables affect "Performance Expectancy" of companies and the intention of using cloud computing. The result from the analysis of data collected in this study is as follows. The study utilized a research model developed on the innovation diffusion theory to identify influences on the adaptation and spreading IT for cloud computing services. Second, this study summarized the characteristics of cloud computing services as a new concept that introduces innovation at its early stage of adaptation for companies. Third, a theoretical model is provided that relates to the future innovation by suggesting variables for innovation characteristics to adopt cloud computing services. Finally, this study identified the factors affecting expectation and the intention to use the cloud computing service for the companies that consider adopting the cloud computing service. As the parameter and dependent variable respectively, the study deploys the independent variables that are aligned with the characteristics of the cloud computing services based on the innovation diffusion model, and utilizes the expectation for performance and Intention to Use based on the UTAUT theory. Independent variables for the research model include Relative Advantage, Complexity, Compatibility, Cost Saving, Trialability, and Observability. In addition, 'Acceptance for Adaptation' is applied as an adjustment variable to verify the influences on the expected performances from the cloud computing service. The validity of the research model was secured by performing factor analysis and reliability analysis. After confirmatory factor analysis is conducted using AMOS 7.0, the 20 hypotheses are verified through the analysis of the structural equation model, accepting 12 hypotheses among 20. For example, Relative Advantage turned out to have the positive effect both on Individual Performance and on Strategic Performance from the verification of hypothesis, while it showed meaningful correlation to affect Intention to Use directly. This indicates that many articles on the diffusion related Relative Advantage as the most important factor to predict the rate to accept innovation. From the viewpoint of the influence on Performance Expectancy among Compatibility and Cost Saving, Compatibility has the positive effect on both Individual Performance and on Strategic Performance, while it showed meaningful correlation with Intention to Use. However, the topic of the cloud computing service has become a strategic issue for adoption in companies, Cost Saving turns out to affect Individual Performance without a significant influence on Intention to Use. This indicates that companies expect practical performances such as time and cost saving and financial improvements through the adoption of the cloud computing service in the environment of the budget squeezing from the global economic crisis from 2008. Likewise, this positively affects the strategic performance in companies. In terms of effects, Trialability is proved to give no effects on Performance Expectancy. This indicates that the participants of the survey are willing to afford the risk from the high uncertainty caused by innovation, because they positively pursue information about new ideas as innovators and early adopter. In addition, they believe it is unnecessary to test the cloud computing service before the adoption, because there are various types of the cloud computing service. However, Observability positively affected both Individual Performance and Strategic Performance. It also showed meaningful correlation with Intention to Use. From the analysis of the direct effects on Intention to Use by innovative characteristics for the cloud computing service except the parameters, the innovative characteristics for the cloud computing service showed the positive influence on Relative Advantage, Compatibility and Observability while Complexity, Cost saving and the likelihood for the attempt did not affect Intention to Use. While the practical verification that was believed to be the most important factor on Performance Expectancy by characteristics for cloud computing service, Relative Advantage, Compatibility and Observability showed significant correlation with the various causes and effect analysis. Cost Saving showed a significant relation with Strategic Performance in companies, which indicates that the cost to build and operate IT is the burden of the management. Thus, the cloud computing service reflected the expectation as an alternative to reduce the investment and operational cost for IT infrastructure due to the recent economic crisis. The cloud computing service is not pervasive in the business world, but it is rapidly spreading all over the world, because of its inherited merits and benefits. Moreover, results of this research regarding the diffusion innovation are more or less different from those of the existing articles. This seems to be caused by the fact that the cloud computing service has a strong innovative factor that results in a new paradigm shift while most IT that are based on the theory of innovation diffusion are limited to companies and organizations. In addition, the participants in this study are believed to play an important role as innovators and early adapters to introduce the cloud computing service and to have competency to afford higher uncertainty for innovation. In conclusion, the introduction of the cloud computing service is a critical issue in the business world.

• 아태비즈니스연구
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• 제12권4호
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• pp.313-329
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• 2021

Purpose - Digital trade, which started in the early 2000s, is showing a sharp increase due to the recent pandemic. However, despite this proliferation, users' acceptance of innovation is very slow. Cloud services are at the center of digital trade activation. This study aims to contribute to the spread of digital trade through empirical analysis of the resistance factors that hinder the use of cloud service-based digital trade using the innovation resistance theory and the status quo bias theory. Design/Methodology/Approach - In order to achieve the research purpose, this study was conducted with 171 entrepreneurs using cloud service-based digital trade. Structural equation model(SEM) was used through empirical analysis. Findings - As a result of the study, it was found that the complexity of technology, perceived risk, compatibility, and trust in service providers had a significant effect on innovation resistance, and policy trust did not affect innovation resistance. Also, security concerns and institutional trust were analyzed to have a significant effect on the trust of service providers. Research Implications - This study is meaningful to help the rapid diffusion of innovative technologies through empirical analysis of factors that lower the intention to accept cloud service-based digital trade.

• Journal of Multimedia Information System
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• 제2권1호
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• pp.143-152
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• 2015

Multimedia services in the cloud have become a popular trend in the big data environment. However, how to efficiently schedule a large number of multimedia services in the cloud is still an open and challengeable problem. Current cloud-based scheduling algorithms exist the following problems: 1) the content of the multimedia is ignored, and 2) the cloud platform is a known parameter, which makes current solutions are difficult to utilize practically. To resolve the above issues completely, in this work, we propose a novel distributed multimedia scheduling to satisfy the objectives: 1) Develop a general cloud-based multimedia scheduling model which is able to apply to different multimedia applications and service platforms; 2) Design a distributed scheduling algorithm in which each user makes a decision based on its local information without knowing the others' information; 3) The computational complexity of the proposed scheduling algorithm is low and it is asymptotically optimal in any case. Numerous simulations have demonstrated that the proposed scheduling can work well in all the cloud service environments.

• 통합자연과학논문집
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• 제6권1호
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• pp.12-15
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• 2013

To combine the micro rain radar and microwave radiometer cloud liquid water, we estimate the cloud physical thickness from the difference between the MTSAT-1R cloud top height and cloud base height of visual observation of Daegwallyeong weather station, and the cloud liquid water path of micro rain radar is obtained by multiplying the liquid water content of micro rain radar and the estimated cloud physical thickness. The trend of microwave radiometer liquid water path agrees with that of the micro rain radar during small precipitation. We study these characteristics of micro rain radar and microwave radiometer for small precipitation to obtain the combined cloud water content of micro rain radar and microwave radiometer, constantly operated regardless to the rainfall.

• International Journal of Computer Science & Network Security
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• 제22권2호
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• pp.290-296
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• 2022

Big Data is a data analysis technology empowered by late advances in innovations and engineering. In any case, big data involves a colossal responsibility of equipment and handling assets, making reception expenses of big data innovation restrictive to little and medium estimated organizations. Cloud computing offers the guarantee of big data execution to little and medium measured organizations. Big Data preparing is performed through a programming worldview known as MapReduce. Normally, execution of the MapReduce worldview requires organized joined stockpiling and equal preparing. The computing needs of MapReduce writing computer programs are frequently past what little and medium measured business can submit. Cloud computing is on-request network admittance to computing assets, given by an external element. Normal arrangement models for cloud computing incorporate platform as a service (PaaS), software as a service (SaaS), framework as a service (IaaS), and equipment as a service (HaaS).

• 디지털융복합연구
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• 제11권3호
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• pp.59-71
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• 2013

클라우드 서비스(아마존 웹서비스 등)를 활용하여 글로벌 경쟁력을 갖춘 중소업체의 온라인 서비스(예. Zynga, 파프리카랩)가 등장하거나 금융시장 분석서비스가 클라우드를 활용하는 등 클라우드의 활용도가 높아지고 있으나, 국내 중소기업의 클라우드 이용은 아직 낮은 수준에 머물고 있다. 특히, PaaS(플랫폼 클라우드)가 성장하면서 모듈화된 인터넷 도구를 손쉽게 활용하여 비즈니스를 개발하는 행태가 증가할 것으로 전망되는 만큼, 국내기업의 IT부문 경쟁력 제고를 위하여 국내외 도입 성공사례를 연구하였다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제15권8호
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• pp.2849-2864
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• 2021

The emerging of cloud data sharing can create great values, especially in multi-cloud environments. However, "data island" between different cloud service providers (CSPs) has drawn trust problem in data sharing, causing contradictions with the increasing sharing need of cloud data users. And how to ensure the data value for both data owner and data user before sharing, is another challenge limiting massive data sharing in the multi-cloud environments. To solve the problems above, we propose a Uniform Encoding and Parsing Framework (UEPF) with blockchain to support trustworthy and valuable data sharing. We design namespace-based unique identifier pair to support data description corresponding with data in multi-cloud, and build a blockchain-based data encoding protocol to manage the metadata with identifier pair in the blockchain ledger. To share data in multi-cloud, we build a data parsing protocol with smart contract to query and get the sharing cloud data efficiently. We also build identifier updating protocol to satisfy the dynamicity of data, and data check protocol to ensure the validity of data. Theoretical analysis and experiment results show that UEPF is pretty efficient.

• The Journal of Asian Finance, Economics and Business
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• 제7권12호
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• pp.275-282
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• 2020

The objectives of this study are to understand the meaning of cloud accounting, to investigate whether it is favorable for performance of the organization and what are the challenges if a country like Bangladesh wants to implement it. Primary data have been collected from 300 respondents selected from the field of accounting, such as accountants, accounting graduates of different universities, teachers and bankers. To measure the reliability and validity of the sample size and data, KMO and Bartlett's test have been adopted and the results proved to be reliable and valid for the study. Regression analysis has been done to find out the positive impact of cloud accounting on organizational performance and negative impact of cloud accounting on existing accounting system of the organization. The results of regression analysis supported our alternative hypotheses that cloud accounting can improve organizational performance, but it has also some negative impacts. Descriptive statistics have been used to find out the probable challenges that may be faced by organizations that want to implement it. This is a pioneering study because there is little research on this topic, thus it is expected to develop awareness about cloud accounting in field of accounting in Bangladesh.

• 신재생에너지
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• 제16권1호
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• pp.25-30
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• 2020

In this study, an SW for the analysis of the wind-turbine vibration characteristics was developed as an application of SaaS cloud infrastructure. A measurement system for power-performance, mechanical load, and gearbox vibration as type-test class was installed at a target MW-class wind turbine, and structural meta and raw data were then acquired into the cloud. Data processing algorithms were developed to provide cloud data to the SW. To operate the SW continuously, raw data was downloaded consistently based on the algorithms. During the SW test, an intermittent long time-delay occurred due to the communication load associated with frequent access to the cloud. To solve this, a compression service for the target raw data was developed in the cloud and more stable data processing was confirmed. Using the compression service, stable big data processing of wind turbines, including gearbox vibration analysis, is expected.