• Atmosphere
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• v.28 no.2
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• pp.211-222
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• 2018

Cloud droplet activation process is well described by $K{\ddot{o}}hler$ theory and several parameterizations based on $K{\ddot{o}}hler$ theory are used in a wide range of models to represent this process. Here, we test the two different method of calculating the solute effect in the $K{\ddot{o}}hler$ equation, i.e., osmotic coefficient method (OSM) and ${\kappa}-K{\ddot{o}}hler$ method (KK). To do that, each method is implemented in the cloud droplet activation parameterization module of WRF-CHEM (Weather Research and Forecasting model coupled with Chemistry) model. It is assumed that aerosols are composed of five major components (i.e., sulfate, organic matter, black carbon, mineral dust, and sea salt). Both methods calculate similar representative hygroscopicity parameter values of 0.2~0.3 over the land, and 0.6~0.7 over the ocean, which are close to estimated values in previous studies. Simulated precipitation, and meteorological variables (i.e., specific heat and temperature) show good agreement with reanalysis. Spatial patterns of precipitation and liquid water path from model results and satellite data show similarity in general, but on regional scale spatial patterns and intensity show some discrepancy. However, meteorological variables, precipitation, and liquid water path do not show significant differences between OSM and KK simulations. So we suggest that the relatively simple KK method can be a good alternative to the OSM method that requires various information of density, molecular weight and dissociation number of each individual species in calculating the solute effect.

• Information Systems Review
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• v.19 no.1
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• pp.75-100
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• 2017

Today, firms are constantly transforming and innovating to survive under the rapidly changing business environment. The introduction of cloud computing services has become popular throughout society as a whole and is expected to result in many changes and developments not only in firms and but also in the public sector subject to innovation. The purpose of this study is to investigate the effect of the characteristics of cloud computing services on the perceived expected performance according to innovativeness based on innovation diffusion theory. The results of the analysis of the data collected from this research are as follows. The convenience and understanding of individuals' work as well as the benefits of cloud computing services to them depend on the innovative trend of cloud computing services. Further, the expectations for personal benefit and those for organizational benefit of cloud computing services are different from each other. Leading firms in the global market have been actively engaged in the utilization of cloud computing services in the public sector as well as in private firms. In consideration of the importance of cloud computing services, using cloud computing services as the target of innovation diffusion research is important. The results of the study are expected to contribute to developing future research models for the diffusion of new technologies, such as big data, digital convergence, and Internet of Things.

• Structural Engineering and Mechanics
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• v.63 no.5
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• pp.639-646
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• 2017

According to the multi-index system of dam safety assessment and the standard of safety, a comprehensive evaluation model for dam safety based on a cloud model is established to determine the basic probability assignment of the Dempster-Shafer theory. The Dempster-Shafer theory is improved to solve the high conflict problems via fusion calculation. Compared with the traditional Dempster-Shafer theory, the application is more extensive and the result is more reasonable. The uncertainty model of dam safety multi-index comprehensive evaluation is applied according to the two theories above. The rationality and feasibility of the model are verified through application to the safety evaluation of a practical arch dam.

• Journal of KIISE:Computer Systems and Theory
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• v.32 no.8
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• pp.411-417
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• 2005

We present a method to reconstruct a canal surface from a point cloud (a set of unorganized points). A canal surface is defined as a swept surface of a moving sphere with varying radii. By using the shrinking and moving least-squares methods, we reduce a point cloud to a thin curve-like point set which can be approximated to the spine curve of a canal surface. The distance between a point in the thin point cloud and a corresponding point in the original point set represents the radius of the canal surface.

• International conference on construction engineering and project management
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• 2015.10a
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• pp.271-275
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• 2015

A variety of evaluation application and initiatives on the adoption of Building Information Modelling (BIM) have been introduced in recent years. Most of which however, focused mainly on evaluating design to construction phase-processes, or BIM utilization performances. Through studying existing publications, it is found that continuous utilization of BIM data throughout the building's life cycle is comparatively less explored or documented. Therefore, this study looks at improving this incomplete life cycle condition with the concept that accumulated BIM data should be carried forward and statistically quantified for cross comparison, in order to facilitate practitioners to better improve the projects the future. Based on this conceptual theory of moving towards a closedloop BIM building life cycle, this study explores, through existing literature, the use of cloud based computing as the means to quantify and adaptively utilize BIM data. Categorization of BIM data relations in adaptive utilization of BIM data is then suggested as a initial step for enhancing cross comparison of BIM data in a cloud environment.

• Korean Management Science Review
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• v.30 no.2
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• pp.11-30
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• 2013

Small and medium-sized enterprises (SMEs) constitute an important part of current industrial economies. Information technologies can be useful strategic weapons for SMEs by enhancing their competitiveness. Categorized as one kind of cloud computing, SaaS is a computing resource and software sharing model which can be accessed via the Internet. Based on virtualization technology, SaaS is expected to improve the efficiency and quality of the IT service level in SMEs. This study attempts to identify the determinants of SaaS adoption intention among Korean SMEs. Through the lens of the theory of planned behavior, this study adopts technological, organizational, environmental factors to explore the determinants of cloud computing adoption intention. The research population is the SMEs that have been funded by the Korean government. Partial least square method was used for empirical analysis of 190 samples collected through on-line survey. The results show that the positive attitude is influenced by business process improvements. Vender support and top management support are positively associated with subjective norm. Vendor support, top management support can relieve perceived behavior control factors. Government support directly influences adoption intention of cloud computing. These findings can provide useful strategy for both SMEs and vendors of SaaS.

• International Journal of Advanced Culture Technology
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• v.12 no.1
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• pp.158-168
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• 2024

With Wenhai big data SaaS cloud platform.2.0, this study analyzed data of 135 news reports relating to Chinese city Chongqing from Yonhap News Agency and ten South Korean mainstream newspapers from May 1^st, 2018 to September 30^th, 2022. Under the framework of Frame Theory, this research conducted data mining and analysis on how Korean mainstream media shaped city image of Chongqing, what kind of city images were shaped from dimensions of politics, economy, society, culture & sports as well as tourism and whether they are consistent with those in Chinese media. At the last part, discussions and suggestions was made.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.14 no.6
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• pp.33-39
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• 2014

An area presenting new opportunities for both legitimate business, as well as criminal organizations, is Cloud computing. This work gives a strong background in current digital forensic science, as well as a basic understanding of the goal of Law Enforcement when conducting digital forensic investigations. These concepts are then applied to digital forensic investigation of cloud environments in both theory and practice, and supplemented with current literature on the subject. Finally, legal challenges with digital forensic investigations in cloud environments are discussed.

• International Journal of Contents
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• v.13 no.2
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• pp.29-34
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• 2017

Cloud computing is becoming an effective and efficient way of computing resources and computing service integration. Through centralized management of resources and services, cloud computing delivers hosted services over the internet, such that access to shared hardware, software, applications, information, and all resources is elastically provided to the consumer on-demand. The main enabling technology for cloud computing is virtualization. Virtualization software creates a temporarily simulated or extended version of computing and network resources. The objectives of virtualization are as follows: first, to fully utilize the shared resources by applying partitioning and time-sharing; second, to centralize resource management; third, to enhance cloud data center agility and provide the required scalability and elasticity for on-demand capabilities; fourth, to improve testing and running software diagnostics on different operating platforms; and fifth, to improve the portability of applications and workload migration capabilities. One of the key features of cloud computing is elasticity. It enables users to create and remove virtual computing resources dynamically according to the changing demand, but it is not easy to make a decision regarding the right amount of resources. Indeed, proper provisioning of the resources to applications is an important issue in IaaS cloud computing. Most web applications encounter large and fluctuating task requests. In predictable situations, the resources can be provisioned in advance through capacity planning techniques. But in case of unplanned and spike requests, it would be desirable to automatically scale the resources, called auto-scaling, which adjusts the resources allocated to applications based on its need at any given time. This would free the user from the burden of deciding how many resources are necessary each time. In this work, we propose an analytical and efficient VM-level scaling scheme by modeling each VM in a data center as an M/M/1 processor sharing queue. Our proposed VM-level scaling scheme is validated via a numerical experiment.

• International Journal of Computer Science & Network Security
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• v.24 no.9
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• pp.50-62
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• 2024

The decision to integrate mobile cloud computing (MCC) in higher education without first defining suitable usage scenarios is a global issue as the usage of such services becomes extensive. Consequently, this study investigates the security determinants of the educational use of mobile cloud computing among universities' students. This study proposes and develops a theoretical model by adopting and modifying the Protection Motivation Theory (PMT). The study's findings show that a significant amount of variance in MCC adoption was explained by the proposed model. MCC adoption intention was shown to be highly influenced by threat appraisal and coping appraisal factors. Perceived severity alone explains 37.8% of students "Intention" to adopt MCC applications, which indicates the student's perception of the degree of harm that would happen can hinder them from using MCC. It encompasses concerns about data security, privacy breaches, and academic integrity issues. Response cost, perceived vulnerability and response efficacy also have significant influence on students "intention" by 18.8%, 17.7%, and 6.7%, respectively.