• Atmosphere
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• v.23 no.4
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• pp.453-470
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• 2013

As a part of the KIAPS Observation Processing System (KOPS), we have developed the modules of satellite radiance data pre-processing and quality control, which include observation operators to interpolate model state variables into radiances in observation space. AMSU-A (Advanced Microwave Sounding Unit-A) level-1d radiance data have been extracted using the BUFR (Binary Universal Form for the Representation of meteorological data) decoder and a first guess has been calculated with RTTOV (Radiative Transfer for TIROS Operational Vertical Sounder) version 10.2. For initial quality checks, the pixels contaminated by large amounts of cloud liquid water, heavy precipitation, and sea ice have been removed. Channels for assimilation, rejection, or monitoring have been respectively selected for different surface types since the errors from the skin temperature are caused by inaccurate surface emissivity. Correcting the bias caused by errors in the instruments and radiative transfer model is crucial in radiance data pre-processing. We have developed bias correction modules in two steps based on 30-day innovation statistics (observed radiance minus background; O-B). The scan bias correction has been calculated individually for each channel, satellite, and scan position. Then a multiple linear regression of the scan-bias-corrected innovations with several predictors has been employed to correct the airmass bias.

• Journal of the Korean earth science society
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• v.30 no.5
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• pp.630-645
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• 2009

The tropopause fold event that took place on January 1, 1997 over mid-region on the Korean Peninsula is examined by means of a numerical simulation based on a Mesoscale Model (MM5). The purpose of this paper is to investigate the effects of moisture in reinforcing a tropopause fold linked to an explosive cyclone. Two types of simulations were carried out; 1) simulations for moist conditions in which full physical and dynamic processes are considered and 2) simulations for dry conditions in which cumulus parameterization and cloud microphysics process are excluded. The results of the moist condition simulations demonstrate that the intensity of the central pressure of the cyclone was overestimated compared with the observed values and that the location of the center and the pressure deepening rates (-17 hPa/12 hr) complied with the observed values. The potential vorticity (PV) anomaly on the isentropic surface at 305 K continued to move in a southeast direction on January 1, 1997 and thus created a single tube of tropopause fold covering the northern and the middle area of the Korean Peninsula and reaching the ground surface at 0300 UTC and 0600 UTC. The results of the dry condition simulations show that the tropopause descended to 500 and 670 hPa in 0300 and 0600 UTC, respectively at the same location for the moist condition simulation; however, there was no deep tropopause fold observed. A comparison of the simulated data between the moist and the dry conditions suggests that a deep tropopause fold should happen when there is sufficient moist in the atmosphere and significantly large PV in the lower atmosphere pulls down the upper atmosphere rather than when the tropopause descends itself due to dynamic causes. Thus, it is estimated that moisture in the atmosphere should have played a crucial role in a deep tropopause fold process.

• Journal of KIISE:Computing Practices and Letters
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• v.14 no.5
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• pp.527-531
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• 2008

For statistical modeling, the model parameters are usually estimated by maximizing a probability measure, such as the likelihood or the posterior. In contrast, a variational Bayesian method treats the parameters of a model as probability distributions and computes optimal distributions for them rather than values. It has been shown that this approach effectively avoids the overfitting problem, which is common with other parameter optimization methods. This paper applies a variational Bayesian technique to surface fitting for height field data. Then, we propose point cloud denoising based on the basic surface fitting technique. Validation experiments and further tests with scan data verify the robustness of the proposed method.

• Journal of Environmental Impact Assessment
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• v.11 no.2
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• pp.79-91
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• 2002

Four dimensional data assimilation (FDDA) technique was considered for 3 dimensional wind field in coastal area and a set of 3 numerical experiments including control experiments has been tested for the case of the synoptic weather pattern of the weak northerly geostrophic wind with the cloud amount of less than 5/10 in autumn. A three dimensional land and sea breeze model with the sea surface temperature (SST) of 290K was performed without nudging the observed wind field and surface temperature of AWS (Automatic Weather System) for the control experiment. The results of the control experiment showed that the horizontal temperature gradient across the coastline was weakly simulated so that the strength of the sea breeze in the model was much weaker than that of observed one. The experiment with only observed horizontal wind field showed that both the pattern of local change of wind direction and the times of starting and ending of the land-sea breeze were fairly well simulated. However, the horizontal wind speed and vertical motion in the convergence zone were weakly simulated. The experiment with nudgings of both the surface temperature and wind speed showed that both the pattern of local change of wind direction and the times of starting and ending of the land-sea breeze were fairly well simulated even though the ending time of the sea breeze was delayed due to oversimulated temperature gradient along the shoreline.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.10
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• pp.3989-4006
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• 2020

The intelligent agriculture monitoring is based on the perception and analysis of environmental data, which enables the monitoring of the production environment and the control of environmental regulation equipment. As the scale of the application continues to expand, a large amount of data will be generated from the perception layer and uploaded to the cloud service, which will bring challenges of insufficient bandwidth and processing capacity. A fog-based offline and real-time hybrid data analysis architecture was proposed in this paper, which combines offline and real-time analysis to enable real-time data processing on resource-constrained IoT devices. Furthermore, we propose a data process-ing algorithm based on the incremental principal component analysis, which can achieve data dimensionality reduction and update of principal components. We also introduce the concept of Squared Prediction Error (SPE) value and realize the abnormal detection of data through the combination of SPE value and data fusion algorithm. To ensure the accuracy and effectiveness of the algorithm, we design a regular-SPE hybrid model update strategy, which enables the principal component to be updated on demand when data anomalies are found. In addition, this strategy can significantly reduce resource consumption growth due to the data analysis architectures. Practical datasets-based simulations have confirmed that the proposed algorithm can perform data fusion and exception processing in real-time on resource-constrained devices; Our model update strategy can reduce the overall system resource consumption while ensuring the accuracy of the algorithm.

• Journal of the Korean Association of Geographic Information Studies
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• v.19 no.2
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• pp.86-97
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• 2016

This study aims to analyze the characteristics of the smart city governance through the multi-layer governance model, which includes administrative governance(AG), technological governance(TG), and global governance(GG). The results of the smart city governance are as follows. Multi-layered governance was modeled to enable cross-checking of each element of the propelling process and types of governance. AG has transitioned from a public partnership to a public-private people partnership(pppp) through a public-private partnership(ppp). TG has the characteristics of information communication technologies(ICTs) - eco technologies(EcoTs) - Spatial technology convergence including physical center, information software platforms such as the CCTV convergence center, and virtualization such as the cloud data center. GG aims at developing killer applications and ICTs-embedded space with intelligent buildings such as a smart city special zone to enable overseas exports. The smart city roadshow and forum have been developed as a platform for overseas exports with competition as well as cooperation.

• Journal of The Korean Astronomical Society
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• v.41 no.2
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• pp.39-47
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• 2008

Spectral line profiles of filaments/prominences to be observed by the Fast Imaging Solar Spectrograph (FISS) are studied. The main spectral lines of interests are $H{\alpha}$, Ca II 8542, and Ca II K. FISS has a high spectral resolving power of $2{\times}10^5$, and supports simultaneous dual-band recording. This instrument will be installed at the 1.6m New Solar Telescope (NST) of Big Bear Solar Observatory, which has a high spatial resolution of 0.065" at 500nm. Adopting the cloud model of radiative transfer and using the model parameters inferred from pre-existing observations, we have simulated a set of spectral profiles of the lines that are emitted by a filament on the disk or a prominence at the limb. Taking into account the parameters of the instrument, we have estimated the photon count to be recorded by the CCD cameras, the signal-to-noise ratios, and so on. We have also found that FISS is suitable for the study of multi-velocity threads in filaments if the spectral profiles of Ca II lines are recorded together with $H{\alpha}$ lines.

• Journal of the Korean Data and Information Science Society
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• v.27 no.4
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• pp.845-854
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• 2016

Sentiment analysis or opinion mining is a technique of text mining employed to identify subjective information or opinions of an individual from documents in blogs, reviews, articles, or social networks. In the literature, only a problem of binary classification of ratings based on review texts in an online review. However, because there can be positive or negative reviews as well as neutral reviews, a multi-class classification will be more appropriate than the binary classification. To this end, we consider the multi-class classification of ratings based on review texts. In the preprocessing stage, we extract words related with ratings using chi-square statistic. Then the extracted words are used as input variables to multi-class classifiers such as support vector machines and proportional odds model to compare their predictive performances.

• Advances in robotics research
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• v.2 no.1
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• pp.45-57
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• 2018

Even though the popularity of projection mapping continues to increase and it is being implemented in more and more settings, most current projection mapping systems are limited to special purposes, such as outdoor events, live theater and musical performances. This lack of versatility arises from the large number of projectors needed and their proper calibration. Furthermore, we cannot change the positions and poses of projectors, or their projection targets, after the projectors have been calibrated. To overcome these problems, we propose a projection mapping method using a projector robot that can perform projection mapping in more general or ubiquitous situations, such as shopping malls. We can estimate a projector's position and pose with the robot's self-localization sensors, but the accuracy of this approach remains inadequate for projection mapping. Consequently, the proposed method solves this problem by combining self-localization by robot sensors with position and pose estimation of projection targets based on a 3D model. We first obtain the projection target's 3D model and then use it to accurately estimate the target's position and pose and thus achieve accurate projection mapping with a projector robot. In addition, our proposed method performs accurate projection mapping even after a projection target has been moved, which often occur in shopping malls. In this paper, we employ Ubiquitous Display (UD), which we are researching as a projector robot, to experimentally evaluate the effectiveness of the proposed method.

• Journal of Digital Convergence
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• v.11 no.10
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• pp.95-102
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• 2013

The paradigm of SW industry has been rapidly changing into mobile and cloud technology environment. Research model based on PEST-SWOT analysis was employed to derive internal and external factors connected with PEST factors through analyzing the current status and problems of SW HRD system in Korea. Survey was conducted by 20 experts who are involved in SW companies, university, and R&D research institute using AHP(Analytic Hierarchy Process) model. The empirical result showed that SW fusion HRD, creativity-oriented university education in the field of software, global education and exchange, and revitalization of SW venture ecosystem are derived as policy visions of SW HRD for smart industry ecosystem. Another findings are that SW fusion HRD, revitalization of SW venture ecosystem, Job Creation through revitalization of SW start-up, Creation of coexistence between SW large enterprises and SMEs, creativity-oriented university education in the field of software, and global education and exchange are presented in order in terms of the importance of policy priority.