• The Bulletin of The Korean Astronomical Society
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• v.35 no.2
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• pp.72.1-72.1
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• 2010

We present infrared and millimeter observations of the active star-forming complex W51. A $1.25\;deg\times1.00\;deg$ region that includes the W51 complex was covered in the J = 2 - 1 transition of the $^{12}CO$ and $^{13}CO$ molecules with the University of Arizona Heinrich Hertz Submillimeter Telescope. We use a statistical equilibrium code to estimate physical properties of the molecular gas. Using Spitzer data we identify young stellar objects (YSOs) and fit model spectral energy distributions to these sources and constrain their physical properties. We compare the molecular cloud morphology with the distribution of infrared and radio continuum sources and find associations between molecular clouds and YSOs. We estimate that about 1% of the cloud mass is currently in YSOs.

• Korean Journal of Remote Sensing
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• v.39 no.6_1
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• pp.1497-1503
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• 2023

To address challenges in classifying clouds and snow cover when calculating ground reflectance in Near-UltraViolet (UV) wavelengths, this study introduces a methodology that combines cloud data from the Geostationary Environmental Monitoring Spectrometer (GEMS) and the Advanced Meteorological Imager (AMI)satellites for snow cover analysis. The proposed approach aims to enhance the quality of surface reflectance calculations, and combined cloud data were generated by integrating GEMS cloud data with AMI cloud detection data. When applied to compute GEMS surface reflectance, this fusion approach significantly mitigated underestimation issues compared to using only GEMS cloud data in snow-covered regions, resulting in an approximately 17% improvement across the entire observational area. The findings of this study highlight the potential to address persistent underestimation challenges in snow areas by employing fused cloud data, consequently enhancing the accuracy of other Level-2 products based on improved surface reflectivity.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.15 no.4
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• pp.257-270
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• 2022

In this paper, we design a smart factory risk improvement system and risk improvement method using AI edge devices. The smart factory risk improvement system collects, analyzes, prevents, and promptly responds to the worker's work performance process in the smart factory using AI edge devices, and can reduce the risk that may occur during work with improving the defect rate when workers perfom jobs. In particular, based on worker image information, worker biometric information, equipment operation information, and quality information of manufactured products, it is possible to set an abnormal risk condition, and it is possible to improve the risk so that the work is efficient and for the accurate performance. In addition, all data collected from cameras and IoT sensors inside the smart factory are processed by the AI edge device instead of all data being sent to the cloud, and only necessary data can be transmitted to the cloud, so the processing speed is fast and it has the advantage that security problems are low. Additionally, the use of AI edge devices has the advantage of reducing of data communication costs and the costs of data transmission bandwidth acquisition due to decrease of the amount of data transmission to the cloud.

• Korean Journal of Remote Sensing
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• v.39 no.6_1
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• pp.1211-1224
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• 2023

Clouds cause many difficult problems in observing land surface phenomena using optical satellites, such as national land observation, disaster response, and change detection. In addition, the presence of clouds affects not only the image processing stage but also the final data quality, so it is necessary to identify and remove them. Therefore, in this study, we developed a new cloud detection technique that automatically performs a series of processes to search and extract the pixels closest to the spectral pattern of clouds in satellite images, select the optimal threshold, and produce a cloud mask based on the threshold. The cloud detection technique largely consists of three steps. In the first step, the process of converting the Digital Number (DN) unit image into top-of-atmosphere reflectance units was performed. In the second step, preprocessing such as Hue-Value-Saturation (HSV) transformation, triangle thresholding, and maximum likelihood classification was applied using the top of the atmosphere reflectance image, and the threshold for generating the initial cloud mask was determined for each image. In the third post-processing step, the noise included in the initial cloud mask created was removed and the cloud boundaries and interior were improved. As experimental data for cloud detection, CAS500-1 L2G images acquired in the Korean Peninsula from April to November, which show the diversity of spatial and seasonal distribution of clouds, were used. To verify the performance of the proposed method, the results generated by a simple thresholding method were compared. As a result of the experiment, compared to the existing method, the proposed method was able to detect clouds more accurately by considering the radiometric characteristics of each image through the preprocessing process. In addition, the results showed that the influence of bright objects (panel roofs, concrete roads, sand, etc.) other than cloud objects was minimized. The proposed method showed more than 30% improved results(F1-score) compared to the existing method but showed limitations in certain images containing snow.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2013.10a
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• pp.556-559
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• 2013

The purpose of the current research is to develop a strategy to activate the domestic Cloud Date Center (CDC), which allows various cloud services as a fundamental infrastructure in the rising cloud market. Specifically, the paper is proceeded based on three steps; (1) in the first step, the authors analyzes the overall CDC market including leading domestic as well as international CDC companies (e.g., EMC, HP, IBM, Samsung SDS, LG CNS, SK C&C) focusing on revenue, firm size, employee numbers, total energy consumption, market share, and so on. (2) In the next step, the study derives strengths and weaknesses based on the results of the first step. These strengths and weaknesses help us to deduct the factors which should be reinforced or complimented for the domestic CDC's competitive advantage in the global CDC market. Finally, considering these strengths and weaknesses in the second step, the authors suggest a strategy to activate the domestic CDC. Thus, this research will focus on the development of the strategic direction for the domestic CDC, which includes a checklist of strengths and weaknesses by analyzing the overall CDC market situation.

• Journal of KIISE
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• v.43 no.5
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• pp.562-568
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• 2016

Point cloud data can be expressed in a specific coordinate system of a data set with a large number of points, to represent any form that generally has different characteristics in the three-dimensional coordinate space. This paper is aimed at finding a cylindrical pipe in the point cloud of the three-dimensional coordinate system using RANSAC, which is faster than the conventional Hough Transform method. In this study, the proposed cylindrical pipe is estimated by combining the results of parameters based on two mathematical models. The two kinds of mathematical models include a sphere and line, searching the sphere center point and radius in the cylinder, and detecting the cylinder with straightening of center. This method can match cylindrical pipe with relative accuracy; furthermore, the process is rapid except for normal estimation and segmentation. Quick cylinders matching could benefit from laser scanning and reverse engineering construction sectors that require pipe real-time estimates.

• 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.

• 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.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.5 no.10
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• pp.1712-1732
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• 2011

Cloud provides dynamically scalable virtualized computing resources as a service over the Internet. To achieve higher resource utilization over virtualization technology, an optimized strategy that deploys virtual machines on physical machines is needed. That is, the total number of active physical host nodes should be dynamically changed to correspond to their resource usage rate, thereby maintaining optimum utilization of physical machines. In this paper, we propose a pattern-based prediction model for resource provisioning which facilitates best possible resource preparation by analyzing the resource utilization and deriving resource usage patterns. The focus of our work is on predicting future resource requests by optimized dynamic resource management strategy that is applied to a virtualized data center in a Cloud computing environment. To this end, we build a prediction model that is based on user request patterns and make a prediction of system behavior for the near future. As a result, this model can save time for predicting the needed resource amount and reduce the possibility of resource overuse. In addition, we studied the performance of our proposed model comparing with conventional resource provisioning models under various Cloud execution conditions. The experimental results showed that our pattern-based prediction model gives significant benefits over conventional models.

• Journal of Digital Convergence
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• v.16 no.7
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• pp.27-34
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• 2018

This study was conducted to identify the contents of major consulting needs of SMEs using Big Data and to suggest the efficiency of operation. The subjects of the study were counseling cases posted on the website of the Business Support Center of the Ministry of SMEs and Startups. To do this, from 2009 to March 2018, we crawled about 7,000 cases of counseling cases, followed by word cloud analysis centering on effective keyword. The main results were as follows: First, the frequency of counseling cases in each field was found in the order of establishment, management strategy, human resources, financial order. Second, in word cloud analysis, the most frequent keyword related to counseling demand were small businesses, exports, methods, procedures, registration and authentication. In this study, we obtained research results that we can improve the efficiency of the policy in real time from a new point of view by conducting big data analysis on public policy.