• Convergence Security Journal
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• v.24 no.2
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• pp.31-38
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• 2024

Recent expansion in cloud service usage has heightened the importance of cloud security. The purpose of this study is to analyze current research trends in the field of cloud security and to derive implications. To this end, R&D project data provided by the National Science and Technology Knowledge Information Service (NTIS) from 2010 to 2023 was utilized to analyze trends in cloud security research. Fifteen core topics in cloud security research were identified using LDA topic modeling and ARIMA time series analysis. Key areas identified in the research include AI-powered security technologies, privacy and data security, and solving security issues in IoT environments. This highlights the need for research to address security threats that may arise due to the proliferation of cloud technologies and the digital transformation of infrastructure. Based on the derived topics, the field of cloud security was divided into four categories to define a technology reference model, which was improved through expert interviews. This study is expected to guide the future direction of cloud security development and provide important guidelines for future research and investment in academia and industry.

• The Journal of Information Systems
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• v.25 no.4
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• pp.37-61
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• 2016

Purpose This study examines firms at various industries to identify key organizational characteristics that positively drive the evaluation of cloud computing. In addition, this study tests the impact of one's evaluation has on the adoption and integration of cloud computing within their respective firm. Design/methodology/approach A total of 172 responses from various firms currently using cloud computing service were analyzed using the structural equation modeling(SEM). Findings Results show that organizational Needs(Mobility and Job Relevance), Perceived Factors(Relative Advantages and Cost Savings), and Organizational Readiness(Technical Knowledge, Financial Supports, and Managerial Supports) have a significant impact on cloud computing evaluation; and evaluation influences its adoption, and integration. However, two variables(IT Performance Gaps and Compatibility) have no significant impact on cloud computing evaluation. Finally, Evolutional Leadership has a significant moderating effect within the relationship among variables in the process of cloud computing implementation.

• Nuclear Engineering and Technology
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• v.54 no.12
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• pp.4715-4721
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• 2022

A comprehensive approach for modeling the pulse height spectra of gamma-ray detectors from passing radioactive cloud in a case of accident at NPP has been developed. It involves modeling the transport of radionuclides in the atmosphere using Lagrangian stochastic model, WRF meteorological processor with an ARW core and GFS data to obtain spatial distribution of radionuclides in the air at a given moment of time. Applying representation of the cloud as superposition of elementary sources of gamma radiation the pulse height spectra are calculated based on data on flux density from point isotropic sources and detector response function. The proposed approach allows us to obtain time-dependent spectra for any complex radionuclide composition of the release. The results of modeling the pulse height spectra of the scintillator detector NaI(Tl) Ø63×63 mm for a hypothetical severe accident at a NPP are presented.

• Journal of Korea Society of Digital Industry and Information Management
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• v.8 no.1
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• pp.99-105
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• 2012

Given the numbers of smartphones, tablets and other mobile devices shipped every day, more and more users are relying on the cloud as the main driver for satisfying their computing needs, whether it is data storage, applications or infrastructure. Mobile cloud computing is simply cloud computing in which at least some of the devices involved are mobile. Each node is owned by a different user and is likely to be mobile. Using mobile hardware for cloud computing has advantages over using traditional hardware. These advantage include computational access to multimedia and sensor data without the need for large network transfer, more efficient access to data stored on other mobile devices and distributed ownership and maintenance of hardware. It is important to predict job execution time in mobile cloud computing because there are many mobile nodes with different capabilities. This paper analyzes the job execution time for mobile cloud computing in terms of network environment and heterogeneous mobile nodes using a mathematical model.

• Journal of KIBIM
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• v.9 no.4
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• pp.62-74
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• 2019

Because the existing BIM platform is based on user services, the focus is on the development of SaaS (Software as a Service), which provides business services online. However, since a harbor is a security facility, the harbor BIM platform is preferably provided in a private form, rather than relying on the infrastructure environment provided by external cloud providers. Therefore, this study analyzes and reviews the main functions to be provided as SaaS services of the harbor BIM platform. The goal is to build a cloud-based harbor BIM platform that can provide this service to users. To this end, we built IaaS (Infrastructure as a Service) environment of the harbor BIM platform based on the open source Open Stack and integrate and develop PaaS environment with Open Shift applied with IaaS. We applied the GPU to the harbor BIM platform to verify the performance of the harbor BIM platform, and found that the rendering and loading times are improved. In particular, it is expected to reduce the cost of introduction and provide it as the basic cloud environment of similar BIM platform for infrastructure facilities.

• Journal of Digital Contents Society
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• v.19 no.5
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• pp.981-993
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• 2018

Smart healthcare is convergence of ICT and healthcare services, and interdisciplinary research has been actively conducted in various fields. The objective of this study is to investigate trends of smart healthcare research using topic modeling and ego network analysis. Text analysis, frequency analysis, topic modeling, word cloud, and ego network analysis were conducted for the abstracts of 2,690 articles in Scopus from 2001 to April 2018. Topic Modeling analysis resulted in eight topics, Topics included "AI in healthcare", "Smart hospital", "Healthcare platform", "Blockchain in healthcare", "Smart health data", "Mobile healthcare", " Wellness care", "Cognitive healthcare". In order to examine the topic modeling results core deeply, we analyzed word cloud and ego network analysis for eight topics. This study aims to identify trends in smart healthcare research and suggest implications for establishing future research direction.

• Journal of Wellbeing Management and Applied Psychology
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• v.5 no.4
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• pp.33-37
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• 2022

Purpose: This study aims to understand the trend and central concept of domestic researches on laughter therapy. For the analysis, this study used total 72 theses verified by inputting the keyword 'laughter therapy' from 2007 to 2021. Research design, data and methodology: This study performed the development and analysis of keyword co-occurrence network, analyzed the types of researches through topic modeling, and verified the visualized word cloud and sociogram. The keyword data that was cleaned through preprocessing, was analyzed in the method of centrality analysis and topic modeling through the 1-mode matrix conversion process by using the NetMiner (version 4.4) Program. Results: The keywords that most appeared for last 14 years were laughter therapy, depression, the elderly, and stress. The five topics analyzed in thesis data from 2007 to 2021 were therapy, cognitive behavior, quality of life, stress, and the elderly. Conclusions: This study understood the flow and trend of research topics of domestic laughter therapy for last 14 years, and there should be continuous researches on laughter therapy, which reflects the flow of time in the future.

• Journal of the Architectural Institute of Korea Planning & Design
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• v.35 no.7
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• pp.53-61
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• 2019

Cloud BIM, which incorporates cloud computing technology and BIM technology, is increasingly used in construction. In particular, the recent trend of cloud services in IT field is to provide customized cloud services according to the characteristics of users. These changes are also linked to the cloud BIM, which is emerging in the construction industry. However, cloud BIM researches and commercial technologies that are currently underway do not reflect these trends, and they provide services through generalized management functions in construction projects. In order to solve these problems, a new type of customized cloud BIM service is needed that can provide cloud services by reflecting the characteristics of the project, customization based on the user's work, and providing the knowledge service. Therefore, this study aims to derive the system requirement function that should be preceded for implementing the customized cloud BIM service, and the target project is selected as the medical facility.

• Knowledge Management Research
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• v.18 no.4
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• pp.237-260
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• 2017

Recently, with the proliferation of smart phones and mobile devices and the increase in the speed of mobile Internet, IT services are increasingly used in smart phones and mobile devices in a different way from the past. That is, a cloud service that downloads and uses data stored in the server in real time is expanding, and as a result, the security due to the continuous Internet connection of the user becomes a problem. In this study, we analyzed the relationship between factors affecting the continuous use of personal cloud service by using technology acceptance model. In addition to the technology acceptance model, confidentiality, privacy, accessibility, innovation, and self-efficacy were extracted from the existing research with emphasis on the characteristics of the cloud service and security factors. Moreover, the difference of intention to use among genders was verified through structural equation modeling with survey data from 262 personal cloud service users.

• Proceedings of the KSRS Conference
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• v.2
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• pp.668-671
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• 2006

Radiative transfer modeling of ice clouds is developed. Ice clouds located near tropopause reflect most of sunlight, thus atmospheric and surface effects can be minimized. Cloud properties such as cloud optical thickness (COT) and effective radius are important parameters to determine the magnitude of reflectance, while atmospheric and surface parameters rarely affect reflectance value. For selected homogeneous cloud pixels of MODerate Resolution Imaging Spectroradiometer (MODIS) observation, reflectances are calculated using MODIS cloud products as inputs of radiative transfer model (RTM). For three types of phase function (Henyey-Greenstein, Garcia-Siewert, Baum) calculated reflectances are compared with observations for validation. All cases show linear relationship between simulated values and measured values, however each represent different bias and slope. The result shows that phase function determine angular distribution of reflectance.