• Korean Journal of Remote Sensing
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• v.29 no.6
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• pp.663-670
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• 2013

Total Vertical Column Density (VCD) of $NO_2$, a key component in air quality and tropospheric chemistry was measured using a ground-based instrument, Pandora, in Seoul from March 2012 to October 2013. The $NO_2$ measurements using Pandora were compared with those obtained by satellite remote sensing from Ozone Monitoring Instrument (OMI) where the intercomparison characteristics were analyzed as a function of measurement geometry, cloud amount and aerosol loading. The negative biases of the OMI $NO_2$ VCD were larger when cloud amount and Aerosol Optical Depth (AOD) were higher. The correlation coefficient between $NO_2$ VCDs from Pandora and OMI was 0.53 for the entire measurement period, whereas the correlation coefficient between the two was 0.74 when the cloud amount and AOD were low (cloud amount<3, AOD<0.4). The low bias of OMI data was associated with the shielding effect of the cloud and the aerosols.

• Atmosphere
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• v.29 no.5
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• pp.609-614
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• 2019

Cloud seeding experiment has been proposed as a way to alleviate severe air pollution problem because, if successful, artificially produced precipitation through cloud seeding could scavenge out some portion of air pollutants. As a first step to verify the practicality of such experiment, seedability of the clouds observed in Seoul is assessed by examining statistical characteristics of some relevant meteorological variables. Analyses of 9 years of Korea Meteorological Agency Seoul station data indicate that as PM₁₀ mass concentration increases, cloud amount, liquid water path, and ice water path decrease, but the difference between temperature and dew point temperature tends to increase. Such finding suggests that cloud seeding becomes less feasible as air pollution becomes more severe in the Seoul metropolitan area, at least in a statistical sense. For some individual severe air pollution events, however, seedable clouds may exist and indeed cloud seeding experiments can be successful. Therefore, detailed investigation on cloud seedability for individual severe air pollution events are highly required to make a concrete assessment of cloud seeding as a way to alleviate severe air pollution problem.

• The Journal of the Korea Contents Association
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• v.22 no.10
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• pp.742-753
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• 2022

Cloud computing, which is rapidly growing as one of the core technologies of the 4th industrial revolution, has become the center of global IT trend change, and Docker, a container-based open source platform, is the mainstream for virtualization technology for cloud computing. Therefore, in this paper, research trends based on Docker containers were compared and analyzed, focusing on studies published from March 2013 to July 2022. As a result of the study, first, the number of papers published by year, domestic and foreign research were steadily increasing. Second, the keywords of the study, in domestic research, Docker, Docker Containers, and Containers were in the order, and in foreign research, Cloud Computing, Containers, and Edge Computing were in the order. Third, in the frequency of publishing institutions to estimate research trends, the utilization was the highest in two papers of the Korean Next Generation Computer Society and the Korean Computer Accounting Society. In the overseas research, IEEE Communications Surveys & Tutorials, IEEE Access, and Computer were in the order. Fourth, in the research method, experiments 78(26.3%) and surveys 32(10.8%) were conducted in domestic research. In foreign research, experiments 128(43.1%) and surveys 59(19.9%) were conducted. In the experiment of implementation research, In domestic research, System 25(8.4%), Algorithm 24(8.1%), Performance Measurement and Improvement 16(5.4%) were in the order, In foreign research, Algorithm 37(12.5%), Performance Measurement and Improvement 17(9.1%), followed by Framework 26(8.8%). Through this, it is expected that it will be used as basic data that can lead the research direction of Docker container-based cloud computing such as research methods, research topics, research fields, and technology development.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.2010-2014
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• 2005

Object detection and parameter estimation in point cloud data is a relevant subject to robotics, reverse engineering, computer vision, and sport mechanics. In this paper a software is presented for fully-automatic object detection and parameter estimation in unordered, incomplete and error-contaminated point cloud with a large number of data points. The software consists of three algorithmic modules each for object identification, point segmentation, and model fitting. The newly developed algorithms for orthogonal distance fitting (ODF) play a fundamental role in each of the three modules. The ODF algorithms estimate the model parameters by minimizing the square sum of the shortest distances between the model feature and the measurement points. Curvature analysis of the local quadric surfaces fitted to small patches of point cloud provides the necessary seed information for automatic model selection, point segmentation, and model fitting. The performance of the software on a variety of point cloud data will be demonstrated live.

• Journal of the Semiconductor & Display Technology
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• v.22 no.3
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• pp.136-141
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• 2023

Artificial intelligence is becoming a global hot topic and is being actively applied in various industrial fields. Not only is artificial intelligence being applied to industrial sites in an on-premises method, but cloud-based artificial intelligence platforms are expanding into "as a service" type. The purpose of this study is to develop and verify a measurement tool for an evaluation framework for the adoption of a cloud-based artificial intelligence platform and test the interrelationships of evaluation variables. To achieve this purpose, empirical testing was conducted to verify the hypothesis using an expanded technology acceptance model, and factors affecting the intention to adopt a cloud-based artificial intelligence platform were analyzed. The results of this study are intended to increase user awareness of cloud-based artificial intelligence platforms and help various industries adopt them through the evaluation framework.

• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.8
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• pp.203-211
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• 2013

Due to the rapid growth of mobile devices and applications, mobile cloud computing is becoming an important platform in the development of cloud services. However, the mobile cloud computing is facing many challenges in terms of the computing resources and communications. One of them is the performance issue between mobile devices and cloud server. In the paper, we implemented a hadoop-based android mobile application, called mobile TPC-C, and used it for evaluating the performance aspect between mobile devices and cloud server. The mobile TPC-C was implemented based on the existing TPC-C, to make it possible to execute on top of android mobile devices. The performance measurement using mobile TPC-C was executed on various transactions while changing the number of mobile clients. By comparing it to the evaluation on the personal PC, we tried to point out the important aspects affecting the performance improvement between mobile clients and cloud server.

• Journal of the Semiconductor & Display Technology
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• v.20 no.2
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• pp.121-125
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• 2021

Cloud service has the characteristic that it must be always available and that it must be able to respond immediately to user requests. This study suggests a method for constructing a proactive and autonomous quality and performance management system to meet these characteristics of cloud services. To this end, we identify quantitative measurement factors for cloud service quality and performance management, define a structure for applying a time series framework to cloud service application quality and performance management for proactive management, and then use big data and artificial intelligence for autonomous management. The flow of data processing and the configuration and flow of big data and artificial intelligence platforms were defined to combine intelligent technologies. In addition, the effectiveness was confirmed by applying it to the cloud service quality and performance management system through a case study. Using the methodology presented in this study, it is possible to improve the service management system that has been managed artificially and retrospectively through various convergence. However, since it requires the collection, processing, and processing of various types of data, it also has limitations in that data standardization must be prioritized in each technology and industry.

• 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.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2008.06a
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• pp.969-970
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• 2008

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.22 no.2
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• pp.179-186
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• 2004

This study describes that the method of precision measurement of vehicle shape and the method of measurement the deformation that it is occurred the reason of accident using industrial photogrammatry. The curved shape is measured using the projection target which is able to acquire the point cloud data. 3D coordinates of the target were able to acquire through object picturing and analysis of coordinates. The acquired point cloud data was done 3D modeling to form the surface with TIN. Also, It able to interpretate a deformation surveying accurately the occurred parts of deformation, then can furnish to the analysis of traffic accident the precise and effective data.