• 한국태양에너지학회:학술대회논문집
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• 2008.04a
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• pp.142-147
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• 2008

Limited fossil fuels and unstable energy supply are considered as one of the critical problems in architecture requiring large amounts of energy. In order to this challenge, environment-friendly architecture design is required. Especially, Application of solar energy as a clean energy source and one kind of renewable energy. Many sites however are mainly concentrated in the developed countries, and are scarcer within the developing world. Simple radiation estimation models using meteorologically observed input parameters are often used in the applications requiring rough estimations of solar radiation. In this paper, measurements of global solar radiation and cloud data hours in climatological locations in South Korea are used to develop an estimation in solar radiation. The results of measured data are compared with the results obtained from equations, internationally accepted correlations.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.12
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• pp.5174-5190
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• 2016

Recent years have witnessed an explosive growth of mobile devices, mobile cloud computing services offered by these devices and the remote clouds behind them. In this paper, we noticed ultra-low latency service, as a type of mobile cloud computing service, requires extremely short delay constraints. Hence, such delay-sensitive applications should be satisfied with strong QoS guarantee. Existing solutions regarding this problem have poor performance in terms of throughput. In this paper, we propose an end-to-end bandwidth resource reservation via software defined scheduling inspired by the famous SDN framework. The main contribution of this paper is the end-to-end resource reservation and flow scheduling algorithm, which always gives priority to delay sensitive flows. Simulation results confirm the advantage of the proposed solution, which improves the average throughput of ultra-low latency flows.

• Journal of Information Technology Applications and Management
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• v.24 no.4
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• pp.117-131
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• 2017

We question whether Korean IT managers consider real options to reduce risks of cloud service implementation. This work investigates the impact of technology risk, relationship risk, economy risk, security risk upon the intention of IT managers to utilize abandon & expansion options. We also analyze moderation effect of centralization level of decision making between these risks and the utilization of real options. Using the survey questionnaire, we empirically find that technology risk, relationship risk and security risk have significant effect upon abandon option and technology risk, relationship risk, and economy upon expansion option. We also find the evidence that centralization level moderates some risks and the direction of moderation effect is to offset the effect of risks on intention to utilize real options.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.150-152
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• 2003

Laser scanned lidar data record 3D surface information in detail. Exploring valuable spatial information from lidar data is a prerequisite task for its applications, such as DEM generation and 3D building model reconstruction. However, the inherent spatial information is implicit in the abundant, densely and randomly distributed point cloud. This paper proposes a novel method to organize point cloud data, so that further analysis or feature extraction can proceed based on a well organized data model. The principle of the proposed algorithm is to segment point cloud into 3D planes. A split and merge segmentation based on the octree structure is developed for the implementation. Some practical airborne and ground lidar data are tested for demonstration and discussion. We expect this data organization could provide a stepping stone for extracting spatial information from lidar data.

• IEMEK Journal of Embedded Systems and Applications
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• v.16 no.5
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• pp.215-223
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• 2021

3D data can be categorized into two parts : Euclidean data and non-Euclidean data. In general, 3D data exists in the form of non-Euclidean data. Due to irregularities in non-Euclidean data such as mesh and point cloud, early 3D deep learning studies transformed these data into regular forms of Euclidean data to utilize them. This approach, however, cannot use memory efficiently and causes loses of essential information on objects. Thus, various approaches that can directly apply deep learning architecture to non-Euclidean 3D data have emerged. In this survey, we introduce various deep learning methods for mesh and point cloud data. After analyzing the operating principles of these methods designed for irregular data, we compare the performance of existing methods for shape classification and segmentation tasks.

• International Journal of Naval Architecture and Ocean Engineering
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• v.12 no.1
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• pp.605-616
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• 2020

The construction quality control of hull blocks is of great significance for shipbuilding. The total station device is predominantly employed in traditional applications, but suffers from long measurement time, high labor intensity and scarcity of data points. In this paper, the Terrestrial Laser Scanning (TLS) device is utilized to obtain an efficient and accurate comprehensive construction information of hull blocks. To address the registration problem which is the most important issue in comparing the measurement point cloud and the design model, an automatic registration approach is presented. Furthermore, to compare the data acquired by TLS device and sparse point sets obtained by total station device, a method for key point extraction is introduced. Experimental results indicate that the proposed approach is fast and accurate, and that applying TLS to control the construction quality of hull blocks is reliable and feasible.

• Annual Conference of KIPS
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• 2013.05a
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• pp.175-178
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• 2013

Mobile Virtual Desktop Infrastructures (mVDI) are gaining popularity in cloud computing by allowing mobile devices to execute their mobile applications in a cloud server instead of relying on physical mobile devices. Consolidating many users into mVDI environment can significantly lower IT management expenses and enables new features such as "available-anywhere" desktops. However, there are many barriers to broad adoption including the slow performance of virtualized I/O, CPU scheduling interference problems. In this paper, we will discuss about mVDI with the current issues, the corresponding solutions and challenges.

• Journal of Korea Society of Digital Industry and Information Management
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• v.10 no.4
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• pp.1-9
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• 2014

Recently, with the enlargement of cloud computing, virtual desktop infrastructure(VDI) can be an alternative of the existing personal computer based information environment. For the case of partially introduced VDI coexisting with personal computer environment, we suggest a virtual folder based approach to control the overall digital contents within an organization with a case of implementation. Although a centralizing device was used for storage and sharing of organization's digital contents, it was not easy to accomplish centralizing digital contents completely. It is tried to prevent users from utilizing their own storage in their personal computers or virtual machines and to use virtual folder which transfer and store digital contents to and in EDMS. The virtual folder system of this paper looks like a real folder in a personal computer, but it is another virtual device for outer storage devices including EDMS. It can be an alternative and reference of digital contents control for future applications of cloud computing.

• IEMEK Journal of Embedded Systems and Applications
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• v.16 no.3
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• pp.99-105
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• 2021

The cloud computing evolution has brought us increasing necessity to manage virtual resources. For this reason, Kubernetes has developed to realize autonomous resource management in a large scale. It provides cloud computing infrastructure to handle cluster creations and deletions in a secure virtual computing environment. In the paper, we provide a monitoring scheme in which users can observe securely encrypted protocols while each Kubernetes component exchanges their packets. Eventually, users can utilize the proposed scheme for debugging as well as monitoring.

• Annual Conference of KIPS
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• 2021.11a
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• pp.128-130
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• 2021

Smart cities collect data from thousands of IoT-based sensor devices for intelligent application-based services. Centralized cloud servers support application tasks with higher computation resources but introduce network latency. Fog layer-based data centers bring data processing at the edge, but fewer available computation resources and poor task allocation strategy prevent real-time data analysis. In this paper, tasks generated from devices are distributed as high resource and low resource intensity tasks. The novelty of this research lies in deploying a virtual node assigned to each cluster of IoT sensor machines serving a joint application. The node allocates tasks based on the task intensity to either cloud-computing or fog computing resources. The proposed Task Allocation Strategy provides seamless allocation of jobs based on process requirements.