• Smart Structures and Systems
• /
• v.30 no.5
• /
• pp.501-511
• /
• 2022

Three-dimensional (3D) models have become crucial for improving civil infrastructure analysis, and they can be used for various purposes such as damage detection, risk estimation, resolving potential safety issues, alarm detection, and structural health monitoring. 3D point cloud data is used not only to make visual models but also to analyze the states of structures and to monitor them using semantic data. This study proposes automating the generation of high-quality 3D point cloud data and removing noise using deep learning algorithms. In this study, large-format aerial images of civilian infrastructure, such as cut slopes and dams, which were captured by drones, were used to develop a workflow for automatically generating a 3D point cloud model. Through image cropping, downscaling/upscaling, semantic segmentation, generation of segmentation masks, and implementation of region extraction algorithms, the generation of the point cloud was automated. Compared with the method wherein the point cloud model is generated from raw images, our method could effectively improve the quality of the model, remove noise, and reduce the processing time. The results showed that the size of the 3D point cloud model created using the proposed method was significantly reduced; the number of points was reduced by 20-50%, and distant points were recognized as noise. This method can be applied to the automatic generation of high-quality 3D point cloud models of civil infrastructures using aerial imagery.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.10 no.4
• /
• pp.1732-1750
• /
• 2016

Recently, Peer-to-Peer (P2P) live streaming assisted by the cloud computing has attracted considerable attention to improve the reliability of the P2P such as the resilience to peer churn and the shortage of upload capacity. The cost of cloud-assistance is comprised of the number of requests issued to the cloud and the amount of data fetched from the cloud. In this paper, we propose three techniques to reduce the cost of such a cloud-assistance.More concretely, in the proposed method, 1) each peer which lost its parent in the overlay can find a new parent by referring to the information registered in the cloud, 2) several peers which proactively fetch chunks from the cloud are dynamically invested, and 3) the number of requests issued to the cloud is reduced by allowing peers to fetch a collection of chunks using a single request. The performance of the proposed method is evaluated by simulation. The simulation results indicate that it reduces the cost of conventional scheme by 46% while guaranteeing the quality of live streaming service.

• KIISE Transactions on Computing Practices
• /
• v.23 no.2
• /
• pp.85-96
• /
• 2017

IoT-Cloud service, integration of Internet of Things (IoT) and Cloud, is becoming a critical model for realizing creative and futuristic application services. Since IoT machines have little computing capacity, it is effective to attaching public Cloud resources for realizing IoT-Cloud service. Furthermore, utilizing containers and adopting a microservice architecture for developing IoT-Cloud service are useful for effective realization. The quality of microservice based IoT-Cloud service is affected by service function chaining which inter-connects each functions. For example, an issue with some of the functions or a bottleneck of inter-connection can degrade the service quality. To ensure functionality of the entire service, various test procedures considering various service environments are required to improve the service continuously. Hence in this paper, we introduce experimental realization of continuous integration based on DevOps and employ application performance monitoring for Node.js based IoT-Cloud service. Then we discuss its effectiveness.

• International Journal of Internet, Broadcasting and Communication
• /
• v.14 no.3
• /
• pp.276-284
• /
• 2022

In this paper, we implemented cloud rendering using WebRTC for high-quality AR and VR services. Cloud rendering is an applied technology of cloud computing. It efficiently handles the rendering of large volumes of 3D content. The conventional VR and AR service is a method of downloading 3D content. The download time is delayed as the 3D content capacity increases. Cloud rendering is a streaming method according to the user's point of view. Therefore, stable service is possible regardless of the 3D content capacity. In this paper, we implemented cloud rendering using WebRTC and analyzed its performance. We compared latency of 100MB, 300MB, and 500MB 3D AR content in 100Mbps and 300Mbps internet environments. As a result of the analysis, cloud rendering showed stable latency regardless of data volume. On the other hand, the conventional method showed an increase in latency as the data volume increased. The results of this paper quantitatively evaluate the stability of cloud rendering. This is expected to contribute to high-quality VR and AR services

• Journal of Korean Society for Quality Management
• /
• v.41 no.3
• /
• pp.381-394
• /
• 2013

Purpose: Nowadays, Mobile Cloud Storage services are used widely. For sustainable use of this service, we need to determine what factors affect satisfaction. Therefore, the purpose of this study is to identify the factors that influence satisfaction. Methods: To analyze factors that influence satisfaction, this study sets the factors into three dimensions such as service quality, perceived risk, and individual characteristics and analyze the causal relationship between influence factors and satisfaction through Structural Equation Model. Results: The results of this study are as follows; among service quality, user interface and reliability influenced satisfaction, but adaptability did not have any influence. Perceived risk of illegal access had a negative influence on satisfaction, while perceived risk of privacy leakage did not have significant influence on satisfaction in perceived risk. At last, self-efficacy had a significant influence on satisfaction. Conclusion: We identified the influence factors that influence satisfaction. Our findings will be necessary for Mobile Cloud Storage service providers to strengthen their service.

• The KIPS Transactions:PartD
• /
• v.19D no.1
• /
• pp.49-62
• /
• 2012

In cloud computing, service providers develop and deploy services with common and reusable features among various applications, service consumers locate and reuse them in building their applications. Hence, reusability is a key intrinsic characteristic of cloud services. Services with high reusability would yield high return-on-investment. Cloud services have characteristics which do not appear in conventional programming paradigms, existing quality models for software reusability would not applicable to services. In this paper, we propose a reusability evaluation suite for cloud services, which includes quality attributes and metrics. A case study is presented to show its applicability.

• Journal of Environmental Science International
• /
• v.31 no.2
• /
• pp.117-129
• /
• 2022

In this study, we investigated the characteristics of the meteorological and environmental conditions for a cloud seeding experiment over the Korean peninsula and estimated the available days for the same. The conditions of available days appropriate for a cloud seeding experiment were classified according to four purposes: water resources, drought relief, forest fire prevention, and air quality improvement. The average number of available days for a cloud seeding experiment were 91.27 (water resources), 45.93-51.11 (drought relief), 40.28-46.00 (forest fire prevention), and 42.19-44.60 days/year (air quality improvement). If six experiments were carried out per available day for a cloud seeding experiment, the number of times cloud seeding experiments could be conducted per year in a continuously operating system were estimated as 547.62 (water resources), 275.58-306.66 (drought relief), 241.68-276.00 (forest fire prevention), and 253.14-267.60 times/year (air quality improvement). From this result, it was possible to determine the appropriate meteorological and environmental conditions and statistically estimate the available days for a cloud seeding experiment. The data on the available days for a cloud seeding experiment might be useful for preparing and performing such an experiment.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.6 no.11
• /
• pp.2764-2783
• /
• 2012

Network virtualization supports future Internet environments and cloud computing. Virtualization can mitigate many hardware restrictions and provide variable network topologies to support variable cloud services. Owing to several advantages such as low cost, high flexibility, and better manageability, virtualization has been widely adopted for use in network virtualization platforms. Among the many issues related to cloud computing, to achieve a suitable cloud service quality we specifically focus on network and performance isolation schemes, which ensure the integrity and QoS of each virtual cloud network. In this study, we suggest a virtual network platform that uses Xen-based virtualization, and implement multiple virtualized networks to provide variable cloud services on a physical network. In addition, we describe the isolation of virtual networks by assigning a different virtualized network ID (VLAN ID) to each network to ensure the integrity of the service contents. We also provide a method for efficiently isolating the performance of each virtual network in terms of network bandwidth. Our performance isolation method supports multiple virtual networks with different levels of service quality.

• The Journal of the Institute of Internet, Broadcasting and Communication
• /
• v.12 no.2
• /
• pp.259-269
• /
• 2012

Listed companies ought to account all transactions and report and disclose their financial statements in accordance with International Financial Reporting Standards (IFRS). To comply with IFRS almost all listed companies installed IFRS system within the companies (on-premise system). This study is trying to identify the effect to Quality Management with on-premise IFRS system. Nowadays, however, Cloud Computing is offered as a replacement of the on-premise system. This study is also trying to identify the effect to Quality Management with Cloud Computing environment instead of on-premise system. This is an empirical study through interviews with, questionnaires to, and statistical analysis of the responses from the professionals and experts who experienced installations of IFRS system.

• Atmosphere
• /
• v.25 no.1
• /
• pp.19-30
• /
• 2015

The Ka-band cloud radar (KCR) has been operated by the National Institute of Meteorological Research (NIMR) of Korea Meteorological Administration (KMA) at Boseong National Center for Intensive Observation of severe weather since 2013. Evaluation of data quality is an essential process to further analyze cloud information. In this study, we estimate the measurement error and the sampling uncertainty to evaluate data quality. By using vertically pointing data, the statistical uncertainty is obtained by calculating the standard deviation of each radar parameter. The statistical uncertainties decrease as functions of sampling number. The statistical uncertainties of horizontal and vertical reflectivities are identical (0.28 dB). On the other hand, the statistical uncertainties of Doppler velocity (spectrum width) are 2.2 times (1.6 times) larger at the vertical channel. The reflectivity calibration of KCR is also performed using X-band vertically pointing radar (VertiX) and 2-dimensional video disdrometer (2DVD). Since the monitoring of calibration values is useful to evaluate radar condition, the variation of calibration is monitored for five rain events. The average of calibration bias is 10.77 dBZ and standard deviation is 3.69 dB. Finally, the statistical characteristics of cloud properties have been investigated during two months in autumn using calibrated reflectivity. The percentage of clouds is about 26% and 16% on September to October. However, further analyses are required to derive general characteristics of autumn cloud in Korea.