• Journal of Korea Water Resources Association
• /
• v.41 no.10
• /
• pp.969-982
• /
• 2008

As hydrological models have been progressively developed, they are recognized as appropriate tools to manage water resources. Especially, the need to evaluate the effects of landuse and climate change on hydrological phenomena has been increased, which requires powerful validation methods for the hydrological models to be employed. As measured streamflow data at many locations may not be available, or include significant errors in application of hydrological models, streamflow data simulated by models only might be used to conduct hydrological analysis. In many cases, reducing errors in model simulations requires a powerful model validation method. In this research, we demonstrated a validation methodology of SWAT model using observed flow in two basins with different physical characteristics. First, we selected two basins, Gap-cheon basin and Yongdam basin located in the Guem River Basin, showing different hydrological characteristics. Next, the methodology developed to estimate parameter values for the Gap-cheon basin was applied for estimating those for the Yongdam basin without calibration a priori, and sought for validation of the SWAT. Application result with SWAT for Yongdam basin showed $R_{eff}$ ranging from 0.49 to 0.85, and $R^{2}$ from 0.49 to 0.84. As well, comparison of predicted flow and measured flow in each subbasin showed reasonable agreement. Furthermore, the model reproduced the whole trends of measured total flow and low flow, though peak flows were rather underestimated. The results of this study suggest that SWAT can be applied for predicting effects of future climate and landuse changes on flow variability in river basins. However, additional studies are recommended to further verify the validity of the mixed method in other river basins.

• Steel and Composite Structures
• /
• v.38 no.5
• /
• pp.547-562
• /
• 2021

This paper aims to explore the mechanical behavior and moment-rotation model of blind bolted joints between concrete-filled double skin steel tubular columns and steel-concrete composite beams. For this type of joint, the inner tube and sandwiched concrete were additionally identified as basic components compared with CFST blind bolted joint. A modified moment-rotation model for this type of connection was developed, of which the compatibility condition and mechanical equilibrium were employed to determine the internal forces of basic components and neutral axis. Following this, load transfer mechanism among the inner tube, sandwiched concrete and outer tube was discussed to assert the action area of the components. Subsequently, assembly processes of basic coefficients in terms of their stiffness and resistances based on the component method by simplifying them as assemblages of springs in series or in parallel. Finally, an experimental investigation on four substructure joints with CFDST columns for validation purposes was carried out to capture the connection details. The predicted results derived from the mechanical models coincided well with the experimental results. It is demonstrated that the proposed mechanical model is capable of evaluating the complete moment-rotation relationships of blind bolted CFDST column composite connections.

• ETRI Journal
• /
• v.42 no.3
• /
• pp.324-332
• /
• 2020

In this paper, a blind symbol timing offset (STO) estimation method is proposed for offset quadrature phase-shift keying (OQPSK) modulated signals, which also works for other linearly modulated signals (LMS) such as binary-PSK, QPSK, 𝜋/4-QPSK, and minimum-shift keying. There are various methods available for blind STO estimation of LMS; however, none work in the case of OQPSK modulated signals. The popular cyclic correlation method fails to estimate STO for OQPSK signals, as the offset present between the in-phase (I) and quadrature (Q) components causes the cyclic peak to disappear at the symbol rate frequency. In the proposed method, a set of close and approximate offsets is used to compensate the offset between the I and Q components of the received OQPSK signal. The STO in the time domain is represented as a phase in the cyclic frequency domain. The STO is therefore calculated by obtaining the phase of the cyclic peak at the symbol rate frequency. The method is validated through extensive theoretical study, simulation, and testbed implementation. The proposed estimation method exhibits robust performance in the presence of unknown carrier phase offset and frequency offset.

• Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
• /
• 2001.06a
• /
• pp.1091-1091
• /
• 2001

Previous reports have shown that Near Infrared Spectroscopy (NIRS) can be used to assess physical and chemical properties of flax fibre and fabric quality. Currently, spinners assess yarn quality mainly based on strength and regularity measurements. There two key characteristics are influenced by quality of raw fibres used, especially the degree of rotting and strength. The aim of this investigation was to evaluate the use of NIRS for assessing quality of weft grade yarn available on the commercial market. In order to develop the NIR calibrations, a range of samples representing poor, medium and good quality weft yarn samples was included in the calibration and validation sample sets. The samples were analysed for physical and chemical parameters including caustic weight loss, fibre fractions, lipid, ash and minerals. A detailed protocol for assessing yarn quality has been developed to maximize the accuracy of the reflectance spectra. The development of partial least squares regression models and validation of the calibration equations using blind samples will be presented and discussed.

• Journal of the Korea Institute of Information Security & Cryptology
• /
• v.28 no.6
• /
• pp.1489-1497
• /
• 2018

Web application services have diversified. At the same time, research on intrusion detection is continuing due to the surge of cyber threats. Also, As a single-defense system evolves into multi-level security, we are responding to specific intrusions by correlating security events that have become vast. However, it is difficult to check the OS, service, web application type and version of the target system in real time, and intrusion detection events occurring in network-based security devices can not confirm vulnerability of the target system and success of the attack A blind spot can occur for threats that are not analyzed for problems and associativity. In this paper, we propose the validation of effectiveness for intrusion detection events using TF-IDF. The proposed scheme extracts the response traffics by mapping the response of the target system corresponding to the attack. Then, Response traffics are divided into lines and weights each line with an TF-IDF weight. we checked the valid intrusion detection events by sequentially examining the lines with high weights.

• Journal of Ginseng Research
• /
• v.37 no.3
• /
• pp.341-348
• /
• 2013

Identification of the origins of Panax ginseng has been issued in Korea scientifically and economically. We describe a metabolomics approach used for discrimination and prediction of ginseng roots from different origins in Korea. The fresh ginseng roots from six ginseng cooperative associations (Gangwon, Gaeseong, Punggi, Chungbuk, Jeonbuk, and Anseong) were analyzed by UPLC-MS-based approach combined with orthogonal projections to latent structure-discriminant analysis multivariate analysis. The ginsengs from Gangwon and Gaeseong were easily differentiated. We further analyzed the metabolomics results in subgroups. Punggi, Chungbuk, Jeonbuk, and Anseong ginseng could be easily differentiated by the first two orthogonal components. As a validation of the discrimination model, we performed blind prediction tests of sample origins using an external test set. Our model predicted their geographical origins as 99.7% probability. The robust discriminatory power and statistical validity of our method suggest its general applicability for determining the origins of P. ginseng samples.

• The Bulletin of The Korean Astronomical Society
• /
• v.45 no.1
• /
• pp.63.2-63.2
• /
• 2020

FLASH is a blind neutral hydrogen (HI) absorption line survey, eventually targeting about 100,000 background radio continuum sources in the entire southern sky using the full 36-antenna of the Australian Square Kilometre Array Pathfinder (ASKAP). Our primary goal is to search for associated and intervening HI absorption lines in the intermediate redshift range 0.4 < z < 1.0. The survey aims to understand the evolution of HI gas in galaxies as well as various physical mechanisms in active galactic nuclei, such as accretion and feedback processes. In this poster, we give an overview of the FLASH survey and present the preliminary results from our first 100-hrs of pilot observations. The latest survey data covers 1,000 square degrees and is ideal for validating observation and data processing in the continuous 300MHz-width low frequency ASKAP band (700-1000MHz). One of the crucial objectives of the pilot survey is to establish the analysis methodology that will be applied to upcoming large absorption surveys in the future. We discuss our data quality validation and present some detections of associated/intervening HI absorption lines. These absorption lines allow us to trace the cold gas properties of active and normal galaxies at higher redshifts where the HI emission line is too weak to be detectable.

• Korean Journal of Remote Sensing
• /
• v.36 no.4
• /
• pp.573-586
• /
• 2020

PM (particulate matter) is of interest to everyone because it can have adverse effects on human health by the infiltration from respiratory to internal organs. To date, many studies have made efforts for the prediction of PM10 and PM2.5 concentrations. Unlike previous studies, we conducted the prediction of tomorrow's PM10 concentration for the Air Korea stations using Chinese PM10 data in addition to the satellite AOD and weather variables. We constructed 230,639 matchups from the raw data over 3 million and built an RF (random forest) model from the matchups to cope with the complexity and nonlinearity. The validation statistics from the blind test showed excellent accuracy with the RMSE (root mean square error) of 9.905 ㎍/㎥ and the CC (correlation coefficient) of 0.918. Moreover, our prediction model showed a stable performance without the dependency on seasons or the degree of PM10 concentration. However, part of coastal areas had a relatively low accuracy, which implies that a dedicated model for coastal areas will be necessary. Additional input variables such as wind direction, precipitation, and air stability should also be incorporated into the prediction model as future work.

• Nuclear Engineering and Technology
• /
• v.42 no.4
• /
• pp.339-364
• /
• 2010

Following a joint OECD/NEA-IAEA-sponsored meeting to define the current role and future perspectives of the application of Computational Fluid Dynamics (CFD) to nuclear reactor safety problems, three Writing Groups were created, under the auspices of the NEA working group WGAMA, to produce state-of-the-art reports on different aspects of the subject. The work of the second group, WG2, was to document the existing assessment databases for CFD simulation in the context of Nuclear Reactor Safety (NRS) analysis, to gain a measure of the degree of quality and trust in CFD as a numerical analysis tool, and to take initiatives to extend the existing databases. The group worked over the period of 2003-2007 and produced a final state-of-the-art report. The present paper summarises the material gathered during the study, illustrating the points with a few highlights. A total of 22 safety issues were identified for which the application of CFD was considered to potentially bring real benefits in terms of better understanding and increased safety. A list of the existing databases was drawn up and synthesised, both from the nuclear area and from other parallel, non-nuclear, industrial activities. The gaps in the technology base were also identified and discussed. In order to initiate new ways of bringing experimentalists and numerical analysts together, an international workshop -- CFD4NRS (the first in a series) -- was organised, a new blind benchmark activity was set up based on turbulent mixing in T-junctions, and a Wiki-type web portal was created to offer online access to the material put together by the group giving the reader the opportunity to update and extend the contents to keep the information source topical and dynamic.

• Journal of Korea Society of Industrial Information Systems
• /
• v.27 no.6
• /
• pp.95-103
• /
• 2022

Quick and accurate understanding of the situation in a severe accident is essential for conducting the appropriate accident management and response using the accident diagnosis information. This study employed deep learning technology to diagnose severe accidents through the major safety parameters transferred from a nuclear power plant (NPP) to AtomCARE. After selecting the major accident scenarios to consider, a learning database was established for particular scenarios affiliated with major scenarios by performing a large number of severe accident analyses using MAAP5 code. The severe accident diagnosis technology, which classifies detailed accident scenarios using the major safety parameters from NPPs, was developed by training it with the established database . Verification and validation were conducted by blind test and principal component analysis. The technology developed in this study is expected to be extended and applied to all severe accident scenarios and be utilized as a base technology for quick and accurate severe accident diagnosis.