• Journal of the Korea Institute of Information and Communication Engineering
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• v.15 no.9
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• pp.1910-1917
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• 2011

In this paper, a cloud computing platform is designed and implemented based on an open source cloud platform, OpenNebula, and Xen hypervisor on each node for efficient computer lab system. For the purpose of convenient management, a web-based user interface has been developed for the cloud virtualization system. Once individual virtual machine is allocated to a user based upon class schedule, each user can access the virtual machine remotely and use appropriate operating system and application programs. The developed system can reduce computer lab upgrade cost, management cost, and administration time considerably.

• Journal of Advanced Navigation Technology
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• v.13 no.5
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• pp.781-786
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• 2009

The cloud computing environment is a new trend of web based application parts. It can be IT business model that is able to easily support learning service and allocate resources through the internet to users. U-learning also is a maximal model with efficiency of the internet based learning. Thus, in this research, we proposed a design of u-learning's teaching and learning model that is applying the internet based learning. Proposal method is to fit u-learning and has 7 steps: Preparing, planning, gathering, learning process, analysis and evaluation, and feedback. We make a cloud u-learning server and cloud LMS to process and manage the service. And We also make a mobile devices meta data to aware the model.

• International Journal of Contents
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• v.12 no.4
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• pp.23-30
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• 2016

For a library to be able provide information services and fulfill its function as a knowledge convergence center capable of responding to various information demands, the development of next-generation information systems based on the latest information and communication technology is needed. The development of mobile information services using portable devices such smart phones and tablet PCs and information systems which incorporate the concepts of cloud computing, SaaS (Software as a Service), annotation and Library2.0 is also required. This paper describes a library information system that utilizes collective intelligence and cloud computing. The information system developed for this study adopts the SaaS-based cloud computing service concept to cope with the shift in the mobile service paradigm in libraries and the explosion of electronic data. The strengths of such a conceptual model include the sharing of resources, support of multi-tenants, and the configuration and support of metadata. The user services are provided in the form of software on-demand. To test the performance of the developed system, the efficiency analysis and TTA certification test were conducted. The results of performance tests, It is encouraging that, at least up to 100MB, the job time is approximately linear and with only a moderate overhead of less than one second. The system also passed the level-3 or higher criteria in the certification test, which includes the SaaS maturity, performance and application program functions.

• The Journal of the Korea institute of electronic communication sciences
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• v.5 no.6
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• pp.672-677
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• 2010

Recently, the efficient management system for large-scale sensor data has been required due to the increasing deployment of large-scale sensor networks. In this paper, we propose a cloud-based sensor data management system with low cast, high scalability, and efficiency. Sensor data in sensor networks are transmitted to the cloud through a cloud-gateway. At this point, outlier detection and event processing is performed. Transmitted sensor data are stored in the Hadoop HBase, distributed column-oriented database, and processed in parallel by query processing module designed as the MapReduce model. The proposed system can be work with the application of a variety of platforms, because processed results are provided through REST-based web service.

• Electronics and Telecommunications Trends
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• v.33 no.5
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• pp.111-120
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• 2018

Agent-based modeling and simulation (ABMS) is a computational method for analyzing research targets through observations of agent-to-agent interactions, and can be applied to multidimensional policy experiments in various fields of social sciences to support policy and decision making. Recently, according to increasing complexity of society and the rapid growth of collected data, the need for high-speed processing is considered to be more important in this field. For this reason, in the ABMS research field, a scalable and large-scale computing infrastructure is becoming an essential element, and cloud computing has been considered a promising infrastructure of ABMS. This paper surveys the technology trends of ABMS tools, cloud computing-based modeling, and simulation studies, and forecasts the use of cloud-computing infrastructure for future modeling and simulation tools. Although fundamental studies are underway to apply and operate cloud computing in the areas of modeling and simulation, new and additional studies are required to devise an optimal cloud computing infrastructure to satisfy the needs of large-scale ABMS.

• KIPS Transactions on Software and Data Engineering
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• v.9 no.1
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• pp.1-10
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• 2020

Service robots providing services according to user's needs in dynamically changing environments should be able to utilize external services such as cloud services. Cloud services are, however, changing and expanding continuously and thus the interface to the services must be general and flexible to adapt to the changes of the functionality and data of the services. In order to facilitate the adaptation of the interface to the changes, a model-based general interface to various cloud services is proposed. In this approach, a general and extensible interface is realized by defining standard service profiles that can be easily extended to adapt to the changed services. Experiments with intelligent service robots show satisfying results exhibiting flexible adaptations to new or changed external services.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2014.10a
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• pp.350-353
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• 2014

The large scale of data and operating systems in the trading environment in the cloud. However, technology is not an easy trading system of cloud-based data interoperability. Partially meets the data transfer rate and also the timeliness of the best trading system on the difficulties. Thus various techniques have been introduced for improving the throughput and low latency minimization problem. But the reality is, and the limits of speed improvements like Socket Direct Protocol, Offload Engine with TCP/IP is the hardware, the introduction effect is also low. In this paper, the proposed trading of the cloud XMDR-DAI based stock system. The proposed Safe Proper Time Method for optimal transmission speed and reliability.

• 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 the Optical Society of Korea
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• v.14 no.4
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• pp.444-450
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• 2010

The traditional approach to inverting aerosol extinction makes use of the assumption of a constant LIDAR ratio in the entire Mie-LIDAR signal profile using the Fernald method. For the large uncertainty in the cloud optical depth caused by the assumed constant LIDAR ratio, an not negligible error of the retrieved aerosol extinction below the cloud will be caused in the backward integration of the Fernald method. A new algorithm to determine aerosol extinction below a cirrus cloud from Mie-LIDAR signals, based on a new cloud boundary detection method and a Mie-LIDAR signal modification method, combined with the backward integration of the Fernald method is developed. The result shows that the cloud boundary detection method is reliable, and the aerosol extinction below the cirrus cloud found by inverting from the modified signal is more efficacious than the one from the measured signal including the cloud-layer. The error due to modification is less than 10% taken in our present example.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.42 no.3
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• pp.623-638
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• 2017

Application fields of cloud technologies have been gradually expanded with development of technology development and diversification of services. Cloud technology is used for investment efficiency, operation efficiency and service competitive advantage in digital broadcasting platform. Recently, Cloud broadcasting platform commercialized for UI(User Interface) and data broadcasting in Korea, and broadcasting service competition becomes fierce. Cloud technology of broadcasting provides remove a service dependency hardware resource and software architecture on STB device, and unified operation of user interface and service using cloud server without legacy separating management of STB types. In this paper, we explain application effects in image based cloud broadcasting service platform.