• Journal of Intelligence and Information Systems
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• v.29 no.1
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• pp.143-174
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• 2023

With the development of deep learning technologies, Artificial Intelligence powered Optical Character Recognition (AI-OCR) has evolved to read multiple languages from various forms of images accurately. For the financial industry, where a large number of diverse documents are processed through manpower, the potential for using AI-OCR is great. In this study, we present a configuration and a design of an AI-OCR modality for use in the financial industry and discuss the platform construction with application cases. Since the use of financial domain data is prohibited under the Personal Information Protection Act, we developed a deep learning-based data generation approach and used it to train the AI-OCR models. The AI-OCR models are trained for image preprocessing, text recognition, and language processing and are configured as a microservice architected platform to process a broad variety of documents. We have demonstrated the AI-OCR platform by applying it to financial domain tasks of document sorting, document verification, and typing assistance The demonstrations confirm the increasing work efficiency and conveniences.

• Korean Journal of Remote Sensing
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• v.36 no.3
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• pp.461-474
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• 2020

Korea launched Geostationary Environmental Monitoring Satellite (GEMS), a UV/visible spectrometer that measure pollution gases on 18 February 2020. Because satellite retrieval is an ill-posed inverse solving process, the validation with ground-based measurements or other satellite measurements is essential to obtain reliable products. For this purpose, satellite-based OMI and OMPS total column ozone (TCO), and ground-based Pandora TCO in Busan and Seoul were selected for future GEMS validation. First of all, the goal of this study is to validate the ground ozone data using characteristics that satellite data provide coherent ozone measurements on a global basis, although satellite data have a larger error than the ground-based measurements. In the cross validation between Pandora and OMI TCO, we have found abnormal deviation in ozone time series from Pandora #29 observed in Seoul. This shows that it is possible to perform inverse validation of ground data using satellite data. Then OMPS TCO was compared with verified Pandora TCO. Both data shows a correlation coefficient of 0.97, an RMSE of less than 2 DU and the OMPS-Pandora relative mean difference of >4%. The result also shows the OMPS-Pandora relative mean difference with SZA, TCO, cross-track position and season have insignificant dependence on those variables.In addition, we showed that appropriate thresholds depending on the spatial resolution of each satellite sensor are required to eliminate the impact of the cloud on Pandora TCO.

• Korean Journal of Remote Sensing
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• v.28 no.2
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• pp.215-226
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• 2012

NASA MODIS GPP provides a useful tool to monitor global terrestrial vegetation productivity. Two major problems of NASA GPP in regional applications are coarse spatial resolution ($1.25^{\circ}{\times}1^{\circ}$) of DAO meteorological data and cloud contamination of MODIS FPAR product. In this study, we improved the NASA GPP by using enhanced input data of high spatial resolution (3 km${\times}$3 km) WRF meteorological data and cloud-corrected FPAR over the North Korea. The improved GPP was utilized to investigate characteristics of GPP interannual variation and spatial patterns from 2000 to 2008. The GPP varied from 645 to 863 $gC\;m^{-2}\;y^{-1}$ in 2000 and 2008, respectively. Mixed forest showed the highest GPP (1,076 $gC\;m^{-2}\;y^{-1}$). Compared to NASA GPP (790 $gC\;m^{-2}\;y^{-1}$);FPAR enhancement increased GPP (861) but utilization of WRF data decreased GPP (710). Enhancements of both FPAR and meteorological input resulted in GPP increase (809) and the improvement was the greatest for mixed forest regions (+10.2%). The improved GPP showed better spatial heterogeneity reflecting local topography due to high resolution WRF data. It is remarkable that the improved and NASA GPPs showed distinctly different interannual variations with each other. Our study indicates improvement of NASA GPP by enhancing input variables is necessary to monitor region-scale terrestrial vegetation productivity.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.10
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• pp.4717-4737
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• 2017

Today, smart grids, smart homes, smart water networks, and intelligent transportation, are infrastructure systems that connect our world more than we ever thought possible and are associated with a single concept, the Internet of Things (IoT). The number of devices connected to the IoT and hence the number of traffic flow increases continuously, as well as the emergence of new applications. Although cutting-edge hardware technology can be employed to achieve a fast implementation to handle this huge data streams, there will always be a limit on size of traffic supported by a given architecture. However, recent cloud-based big data technologies fortunately offer an ideal environment to handle this issue. Moreover, the ever-increasing high volume of traffic created on demand presents great challenges for flow management. As a solution, flow aggregation decreases the number of flows needed to be processed by the network. The previous works in the literature prove that most of aggregation strategies designed for smart grids aim at optimizing system operation performance. They consider a common identifier to aggregate traffic on each device, having its independent static aggregation policy. In this paper, we propose a dynamic approach to aggregate flows based on traffic characteristics and device preferences. Our algorithm runs on a big data platform to provide an end-to-end network visibility of flows, which performs high-speed and high-volume computations to identify the clusters of similar flows and aggregate massive number of mice flows into a few meta-flows. Compared with existing solutions, our approach dynamically aggregates large number of such small flows into fewer flows, based on traffic characteristics and access node preferences. Using this approach, we alleviate the problem of processing a large amount of micro flows, and also significantly improve the accuracy of meeting the access node QoS demands. We conducted experiments, using a dataset of up to 100,000 flows, and studied the performance of our algorithm analytically. The experimental results are presented to show the promising effectiveness and scalability of our proposed approach.

• Journal of Advanced Marine Engineering and Technology
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• v.39 no.7
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• pp.744-753
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• 2015

This paper presents the results of research on developing marine unified communications to provide VoIP service based on marine satellites. With the recent popularity of smart-phones and other mobile devices, the demand for Internet-based wired and wireless unified technology has been growing in marine environments, and increasing interest is being directed to VoIP products and service models with high price competitiveness and the ability to deliver a variety of services. In this regard, this research designed three instruments, developed their unit modules, and verified their performances. These three instruments included the following: (1) a marine VoIP module equipped with an analogue gateway that can be linked to the existing devices used in vessels, which is more than 80% smaller than that of a land system; (2) a text/voice/video engine for marine satellite communications that runs on technology that minimizes communication data usage, which is a core technology for a marine VoIP service; and (3) a unified communication service that can support multilateral cloud-based message conversations, telephone number-based call functions, and voice/video calling between a private space in a ship and shore.

• KIISE Transactions on Computing Practices
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• v.24 no.3
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• pp.129-137
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• 2018

NVMe(Non-Volatile Memory Express) SSD(Solid State Drive) is a high-performance storage that makes use of flash memory as a storage cell, PCIe as an interface and NVMe as a protocol on the interface. It supports multiple I/O queues which makes it feasible to process parallel-I/Os on multi-core environments and to provide higher bandwidth than SATA SSDs. Hence, NVMe SSD is considered as a next generation-storage for data-center and cloud computing system. However, in the virtualization system, the performance of NVMe SSD is not fully utilized due to the bottleneck of the software I/O stack. Especially, when it uses I/O stack of the hypervisor or the host operating system like Xen and KVM, I/O performance degrades seriously due to doubled-I/O stack between host and virtual machine. In this paper, we propose a new I/O engine, called Direct-AIO (Direct-Asynchronous I/O) engine, that can access NVMe SSD directly for I/O performance improvements on QEMU emulator. We develop our proposed I/O engine and analyze I/O performance differences between the existed I/O engine and Direct-AIO engine.

• Journal of the Institute of Electronics and Information Engineers
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• v.52 no.1
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• pp.69-78
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• 2015

Recently, due to the development of next-generation computing devices and high-performance network, VDI (Virtual Desktop Infrastructure) is receiving a great deal of attention from IT market as an essential part of cloud computing. VDI enables to host multiple, individual virtual machines that are provisioned from servers located at the data center by using hypervisor. One of the critical issues related to VDI is to reduce the performance difference between virtual machines and physical ones. In this paper, we present a real-time VM monitoring system, called SETMOV, that is able to collect the real-time resource usage information. We also present the performance results using iozone to verify SETMOV.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2015.05a
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• pp.903-906
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• 2015

Over the recent industry -wide virtual world and the real world, broadcasting and telecommunications, IT technology and traditional industries, such as the fusion research has been conducted in a variety of fields. And training in the field of education is changing the paradigm of creativity to break the intrusive training center. In addition, the quality of interactive educational content technology to foster self-directed future talent is a situation that is required. The market has already surpassed the smartphone PC, smart devices and e-learning technologies are appearing new service called 'smart learning' as a new form of convergence of the educational system. In this paper, based on the direct development of a content authoring applications and Web sites, and cloud environments to the students collect and analyze patterns. Utilizing this information, we studied the curation service plans that recommend the appropriate content to fit the tastes of the learner.

• Journal of Environmental Science International
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• v.26 no.5
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• pp.621-638
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• 2017

Meteorological characteristics related to variations in ozone ($O_3$) concentrations in the Korean peninsula before, during, and after Typhoon Talas (1112) were analyzed using both observation data and numerical modeling. This case study takes into account a high $O_3$ episode (e.g., a daily maximum of ${\geq}90ppb$) without rainfall. Before the typhoon period, high $O_3$ concentrations in the study areas (e.g., Daejeon, Daegu, and Busan) resulted from the combined effects of stable atmospheric conditions with high temperature under a migratory anticyclone (including subsiding air), and wind convergence due to a change in direction caused by the typhoon. The $O_3$ concentrations during the typhoon period decreased around the study area due to very weak photochemical activity under increased cloud cover and active vertical dispersion under a low pressure system. However, the maximum $O_3$ concentrations during this period were somewhat high (similar to those in the normal period extraneous to the typhoon), possibly because of the relatively slow photochemical loss of $O_3$ by a $H_2O+O(^1D)$ reaction resulting from the low air temperature and low relative humidity. The lowest $O_3$ concentrations during the typhoon period were relatively high compared to the period before and after the typhoon, mainly due to the transport effect resulting from the strong nocturnal winds caused by the typhoon. In addition, the $O_3$ increase observed at night in Daegu and Busan was primarily caused by local wind conditions (e.g., mountain winds) and atmospheric stagnation in the wind convergence zone around inland mountains and valleys.

• Atmosphere
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• v.22 no.2
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• pp.209-219
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• 2012

Extreme heavy snowfall episodes have been investigated in case of accumulated snowfall amount larger than 50 cm during the past ten years, in order to understand the association of low-level stability with heavy snowfall in the Yeongdong region. In general, the selected 4 events have similar synoptic setting such as the Siberian High extended to East Sea along with the Low passing by the southern Korean Peninsula, eventually inducing easterly in the Yeongdong region. Specifically moist-adiabatically neutral layer has been observed during the heavy snowfall period, which was easily identified using vertical profiles of equivalent potential temperature observed at Sokcho, whereas convective unstable layer has been formed over the East sea due to relatively warm sea surface temperature (SST) about $8{\sim}10^{\circ}C$ and lower temperature around 1~2 km above the surface, obtained from RDAPS. Difference of equivalent potential temperature between 850 hPa and surface as well as difference between air and sea temperatures altogether gradually increased before the snowfall period. Instability-induced moisture supply to the atmosphere from the East sea, being cooled and saturated by the upper cold surge, would make low-level ice cloud, and eventually move inland by the easterly flow. Heavy snowfall will be enhanced in association with low-level convergence by surface friction and upslope wind against Taebaek mountains. This study emphasizes the importance of low level stability in the Yeongdong region using the radiosonde sounding and RDAPS data, which should quantitatively be examined through numerical model as well as heat and moisture supply from the ocean.