• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.10
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• pp.4678-4702
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• 2018

Traffic Matrix estimation has always caught attention from researchers for better network management and future planning. With the advent of high traffic loads due to Cloud Computing platforms and Software Defined Networking based tunable routing and traffic management algorithms on the Internet, it is more necessary as ever to be able to predict current and future traffic volumes on the network. For large networks such origin-destination traffic prediction problem takes the form of a large under- constrained and under-determined system of equations with a dynamic measurement matrix. Previously, the researchers had relied on the assumption that the measurement (routing) matrix is stationary due to which the schemes are not suitable for modern software defined networks. In this work, we present our Compressed Sensing with Dynamic Model Estimation (CS-DME) architecture suitable for modern software defined networks. Our main contributions are: (1) we formulate an approach in which measurement matrix in the compressed sensing scheme can be accurately and dynamically estimated through a reformulation of the problem based on traffic demands. (2) We show that the problem formulation using a dynamic measurement matrix based on instantaneous traffic demands may be used instead of a stationary binary routing matrix which is more suitable to modern Software Defined Networks that are constantly evolving in terms of routing by inspection of its Eigen Spectrum using two real world datasets. (3) We also show that linking this compressed measurement matrix dynamically with the measured parameters can lead to acceptable estimation of Origin Destination (OD) Traffic flows with marginally poor results with other state-of-art schemes relying on fixed measurement matrices. (4) Furthermore, using this compressed reformulated problem, a new strategy for selection of vantage points for most efficient traffic matrix estimation is also presented through a secondary compression technique based on subset of link measurements. Experimental evaluation of proposed technique using real world datasets Abilene and GEANT shows that the technique is practical to be used in modern software defined networks. Further, the performance of the scheme is compared with recent state of the art techniques proposed in research literature.

• Journal of Life Science
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• v.31 no.1
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• pp.100-108
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• 2021

In the oral cavity, there are hundreds of microbial species that exist as planktonic cells or are incorporated into biofilms. The accumulation and proliferation of pathogenic bacteria in the oral biofilm can lead to caries and periodontitis, which are typical oral diseases. The oral bacteria in the biofilm not only can resist environmental stress inside the oral cavity, but also have a 1,000 times higher resistance to antibiotics than planktonic cells by genes exchange through the interaction between cells in the oral biofilm. Therefore, if the formation of oral biofilm is suppressed or removed, oral diseases caused by bacterial infection can be more effectively prevented or treated. In particular, since oral biofilms have the characteristic of forming a biofilm by gathering several bacteria, quorum sensing, a signaling system between cells, can be a target for controlling the oral biofilm. In addition, a method of inhibiting biofilm formation by using arginine, an alkali-producing substrate of oral bacteria, is used to convert the distribution of oral microorganisms into an environment similar to that of healthy teeth or inhibit the secretion of glucosyltransferase by S. mutans to inhibit the formation of non-soluble glucans. It can be a target to control oral biofilm. This method of inhibiting or removing the oral biofilm formation rather than inducing the death of pathogenic bacteria in the oral cavity will be a new strategy that can selectively prevent or therapeutic avenues for oral diseases including dental caries.

• Korean Journal of Remote Sensing
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• v.39 no.6_3
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• pp.1679-1692
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• 2023

South Korea is a country that emits a large amount of pollutants as a result of population growth and industrial development and is also severely affected by transboundary air pollution due to its geographical location. As pollutants from both domestic and foreign sources contribute to air pollution in Korea, the location of air pollutant emission sources is crucial for understanding the movement and distribution of pollutants in the atmosphere and establishing national-level air pollution management and response strategies. Based on this background, this study aims to effectively acquire spatial information on domestic and international air pollutant emission sources, which is essential for analyzing air pollution status, by utilizing high-resolution optical satellite images and deep learning-based image segmentation models. In particular, industrial parks and quarries, which have been evaluated as contributing significantly to transboundary air pollution, were selected as the main research subjects, and images of these areas from multi-purpose satellites 3 and 3A were collected, preprocessed, and converted into input and label data for model training. As a result of training the U-Net model using this data, the overall accuracy of 0.8484 and mean Intersection over Union (mIoU) of 0.6490 were achieved, and the predicted maps showed significant results in extracting object boundaries more accurately than the label data created by course annotations.

• Korean Journal of Remote Sensing
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• v.40 no.2
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• pp.203-217
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• 2024

The Land Use, Land-Use Change and Forestry (LULUCF) sector of the National Greenhouse Gas Inventory is crucial for obtaining data on carbon sinks, necessitating accurate estimations. This study analyzes cases of countries applying the LULUCF sector at the Tier 3 level to propose enhanced methodologies for carbon sink estimation. In nations like Japan and Western Europe, satellite spatial information such as SPOT, Landsat, and Light Detection and Ranging (LiDAR)is used alongside national statistical data to estimate LULUCF. However, in Korea, the lack of land use change data and the absence of integrated management by category, measurement is predominantly conducted at the Tier 1 level, except for certain forest areas. In this study, Space-borne LiDAR Global Ecosystem Dynamics Investigation (GEDI) was used to calculate forest canopy heights based on Relative Height 100 (RH100) in the cities of Icheon, Gwangju, and Yeoju in Gyeonggi Province, Korea. These canopy heights were compared with the 1:5,000 scale forest maps used for the National Inventory Report in Korea. The GEDI data showed a maximum canopy height of 29.44 meters (m) in Gwangju, contrasting with the forest type maps that reported heights up to 34 m in Gwangju and parts of Icheon, and a minimum of 2 m in Icheon. Additionally, this study utilized Ordinary Least Squares(OLS)regression analysis to compare GEDI RH100 data with forest stand heights at the eup-myeon-dong level using ArcGIS, revealing Standard Deviations (SDs)ranging from -1.4 to 2.5, indicating significant regional variability. Areas where forest stand heights were higher than GEDI measurements showed greater variability, whereas locations with lower tree heights from forest type maps demonstrated lower SDs. The discrepancies between GEDI and actual measurements suggest the potential for improving height estimations through the application of high-resolution remote sensing techniques. To enhance future assessments of forest biomass and carbon storage at the Tier 3 level, high-resolution, reliable data are essential. These findings underscore the urgent need for integrating high-resolution, spatially explicit LiDAR data to enhance the accuracy of carbon sink calculations in Korea.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.1915-1919
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• 2004

In this paper, we propose a new discrete-time predictive current controller for a PMSM(Permanent Magnet Synchronous Motor). The main objectives of the current controllers are to ensure that the measured stator currents tract the command values accurately and to shorten the transient interval as much as possible, in order to obtain high-performance of ac drive system. The conventional predictive current controller is hard to implement in full digital current controller since a finite calculation time causes a delay between the current sensing time and the time that it takes to apply the voltage to motor. A new control strategy in this paper is seen the scheme that gets the fast adaptation of transient current change, the fast transient response tracking and is proposed simplified calculation. Moreover, the validity of the proposed method is demonstrated by numerical simulations and the simulation results will be verified the improvements of predictive controller and accuracy of the current controller.

• Molecules and Cells
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• v.39 no.11
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• pp.777-782
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• 2016

The innate immune system has evolved to detect and destroy invading pathogens before they can establish systemic infection. To successfully eradicate pathogens, including viruses, host innate immunity is activated through diverse pattern recognition receptors (PRRs) which detect conserved viral signatures and trigger the production of type I interferon (IFN) and pro-inflammatory cytokines to mediate viral clearance. Viral persistence requires that viruses co-opt cellular pathways and activities for their benefit. In particular, due to the potent antiviral activities of IFN and cytokines, viruses have developed various strategies to meticulously modulate intracellular innate immune sensing mechanisms to facilitate efficient viral replication and persistence. In this review, we highlight recent advances in the study of viral immune evasion strategies with a specific focus on how Kaposi's sarcoma-associated herpesvirus (KSHV) effectively targets host PRR signaling pathways.

• Proceedings of the KSRS Conference
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• 1999.11a
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• pp.198-203
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• 1999

Korea Multi-Purpose Satellite-1 (KOMPSAT-1) is developed by the Korea Aerospace Research Institute (KARI) with the aid of TRW and will be launched on the Nov. 24, 1999 at the Vandenberg Air Base in CA, U.S, Now, the satellite application group in KARI is preparing for the service with the KOMPSAT-1 satellite data. For the purpose of supplying good service to the users, data application planning has to be established before launching satellite. To use satellite data effectively, KARI makes a plan for data policy, data price, mission planning, and commercializing strategy. This study was carried out with the purpose of effective use of satellite data. For this purpose, KARI makes a user group first. There are 58 user groups to use KOMPSAT-1 data for public welfare and research sectors. These user groups include government, public corporations, institutes, and universities. KARI will offer the service to users through online using Internet. Secondly, KARI makes a policy for the priority of KOMPSAT-1 missions. These are classified by the mission priority, payloads, and operational states etc. Thirdly, KARI will make data policy and data price of KOMPSAT- 1 based on the basic master 1)tan. Especially, data price will be determined at trte KOMPSAT-1 committee including Ministry of Science and Technology (MOST). KARI is also trying to commercialize the data with the domestic and foreign companies to expand the use of KOMPSAT-1 data in the industries sector. Afterward in this study, KARI will continue the improvement for the effective distribution of KOMPSAT-1 data for all users.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.39A no.12
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• pp.756-763
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• 2014

In this paper, we introduce a new sparse signal recovery algorithm referred to as the matching pursuit with greedy tree search (GTMP). The tree search in our proposed method is implemented to minimize the cost function to improve the recovery performance of sparse signals. In addition, a pruning strategy is employed to each node of the tree for efficient implementation. In our performance guarantee analysis, we provide the condition that ensures the exact identification of the nonzero locations. Through empirical simulations, we show that GTMP is effective for sparse signal reconstruction and outperforms conventional sparse recovery algorithms.

• Korean Journal of Agricultural and Forest Meteorology
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• v.7 no.1
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• pp.4-14
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• 2005

CarboKorea and HydroKorea are the domestic projects aiming to improve our understanding of carbon and water cycles in a typical Korean forest located in a complex terrain with a watershed connected to large rivers. The ultimate goal is to provide a nowcasting of these cycles for the whole Peninsula. The basic strategy to achieve such goal is through the inter- and multi-disciplinary studies that synthesize the in-situ field observation, modeling and remote sensing technology. The challenge is the fact that natural ecosystems are nonlinear and heterogeneous with a wide range of spatio-temporal scales causing the variations of mass and energy exchanges from a leaf to landscape scales. Our paradigm now shifts from temporal variation at a point to spatial patterns and from spatial homogeneity to complexity of water and carbon at multiple scales. Yet, a large portion of our knowledge about land-atmosphere interactions has been established based on tower observations, indicating that the development of scaling logics holds the key to the success of CarboKorea and HydroKorea. Here, we review the pioneering work of FIFE (First ISLSCP Field Experiment) on scaling issues in a temperate grassland and discuss the lessons from it for the application to Gwangneung forest site.

• Proceedings of the KIEE Conference
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• 2005.07d
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• pp.2631-2633
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• 2005

In this paper, we propose a new discrete-time predictive current controller for a PMLSM(permanent magnet linear synchronous motor). The main objectives of the current controllers are that the measured stator current is tracked the command current value accurately and the transient interval is shorten as much as possible, in order to obtain high-performance of ac drive system. The conventional predictive current controller is hard to implement in full digital current controller since a finite calculation time causes a delay between the current sensing time and the time that take to apply the voltage to motor. A new control strategy is the scheme that gets the fast adaptation of transient current change, the fast transient response tracking. Moreover, the simulation results will be verified the improvements of predictive controller and accuracy of the current controller.