• The Bulletin of The Korean Astronomical Society
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• v.44 no.1
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• pp.61.4-61.4
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• 2019

The key science goal of the KMTNet Supernova Program (KSP) is to detect and study the early explosions of supernovae using one fifth of the KMTNet time. The BVI-band observations of the nearby target fields mostly closer than 30 Mpc distance and the follow-up spectroscopy provide valuable information on the early phase of the supernovae. These data can also be used for the studies of optical transients such as novae, dwarf novae, variable stars, and active galactic nuclei. Stacked images of several hundred images obtained from the time domain observations can be used for the search of low surface brightness galaxies reaching $28mag\;arcsec^{-2}$. Results and status of the KSP including ${\geq}20$ infant supernovae and ${\geq}100$ faint dwarf galaxies will be presented in this talk.

• International Journal of Naval Architecture and Ocean Engineering
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• v.13 no.1
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• pp.136-146
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• 2021

This paper aims to numerically estimate the dynamic ice load on a conical structure. The Discrete Element Method (DEM) is employed to model the level ice as the assembly of numerous spherical particles. To mimic the realistic fracture mechanism of ice, the parallel bonding method is introduced. Cases with four different ice drifting velocities are considered in time domain. For validation, the statistics of time-varying ice forces and their frequencies obtained by numerical simulations are extensively compared against the physical model-test results. Ice properties are directly adopted from the targeted experimental test set up. The additional parameters for DEM simulations are systematically determined by a numerical three-point bending test. The findings reveal that the numerical simulation estimates the dynamic ice force in a reasonably acceptable range and its results agree well with experimental data.

• Journal of Ocean Engineering and Technology
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• v.30 no.3
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• pp.161-168
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• 2016

This paper presents a methodology through which the time series of the dynamic response of mooring line tension can be predicted without relying on a time-consuming nonlinear time-domain analysis. The mooring line tension for the target short-term sea states was predicted using a Hammerstein-Wiener model, a popular system identification scheme, based upon the pre-calculated motion-tension time history data for some selected short-term sea states that do not overlap with the targeted ones. The obtained mooring line tension was further processed, and a fatigue damage comparison was made between the predicted and calculated values. The results showed that the predicted time series of the mooring line tension matched the calculated one fairly well. Thus, it is expected that the methodology may be employed to enhance the efficiency of mooring line tension analysis.

• The KIPS Transactions:PartB
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• v.13B no.2 s.105
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• pp.133-138
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• 2006

Learning with Attribute Value Taxonomies (AVT) has shown that it is possible to construct accurate, compact and robust classifiers from a partially missing dataset (dataset that contains attribute values specified with different level of precision). Yet, in many cases AVTs are generated from experts or people with specialized knowledge in their domain. Unfortunately these user-provided AVTs can be time-consuming to construct and misguided during the AVT building process. Moreover experts are occasionally unavailable to provide an AVT for a particular domain. Against these backgrounds, this paper introduces an AVT generating method called GA-AVT-Learner, which finds a near optimal AVT with a given training dataset using a genetic algorithm. This paper conducted experiments generating AVTs through GA-AVT-Learner with a variety of real world datasets. We compared these AVTs with other types of AVTs such as HAC-AVTs and user-provided AVTs. Through the experiments we have proved that GA-AVT-Learner provides AVTs that yield more accurate and compact classifiers and improve performance in learning missing data.

• Earthquakes and Structures
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• v.10 no.1
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• pp.53-71
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• 2016

Unconventional computer vision and image processing techniques offer significant advantages for experimental applications to shaking table testing, as they allow the overcoming of most typical problems of traditional sensors, such as encumbrance, limitations in the number of devices, range restrictions and risk of damage of the instruments in case of specimen failure. In this study, a 3D motion optical system was applied to analyze shake table tests carried out, up to failure, on a natural-scale masonry structure retrofitted with steel reinforced grout (SRG). The system makes use of wireless passive spherical retro-reflecting markers positioned on several points of the specimen, whose spatial displacements are recorded by near-infrared digital cameras. Analyses in the time domain allowed the monitoring of the deformations of the wall and of crack development through a displacement data processing (DDP) procedure implemented ad hoc. Fundamental frequencies and modal shapes were calculated in the frequency domain through an integrated methodology of experimental/operational modal analysis (EMA/OMA) techniques with 3D finite element analysis (FEA). Meaningful information on the structural response (e.g., displacements, damage development, and dynamic properties) were obtained, profitably integrating the results from conventional measurements. Furthermore, the comparison between 3D motion system and traditional instruments (i.e., displacement transducers and accelerometers) permitted a mutual validation of both experimental data and measurement methods.

• Journal of information and communication convergence engineering
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• v.22 no.1
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• pp.33-43
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• 2024

Automated text summarization (ATS) systems rely on language resources as datasets. However, creating these datasets is a complex and labor-intensive task requiring linguists to extensively annotate the data. Consequently, certain public datasets for ATS, particularly in languages such as Thai, are not as readily available as those for the more popular languages. The primary objective of the ATS approach is to condense large volumes of text into shorter summaries, thereby reducing the time required to extract information from extensive textual data. Owing to the challenges involved in preparing language resources, publicly accessible datasets for Thai ATS are relatively scarce compared to those for widely used languages. The goal is to produce concise summaries and accelerate the information extraction process using vast amounts of textual input. This study introduced ThEconSum, an ATS architecture specifically designed for Thai language, using economy-related data. An evaluation of this research revealed the significant remaining tasks and limitations of the Thai language.

• Proceedings of the Korea Institutes of Information Security and Cryptology Conference
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• 2006.06a
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• pp.123-132
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• 2006

Biometric-based authentication can provide strong security guarantee about the identity of users. However, security of biometric data is particularly important as the compromise of the data will be permanent. To protect the biometric data, we need to store it in a non-invertible transformed version. Thus, even if the transformed version is compromised, the actual biometric data remains safe. In this paper, we propose an approach to protect finger-print templates by using the idea of the fuzzy vault. Fuzzy vault is a recently developed cryptographic construct to secure critical data with the fingerprint data in a way that only the authorized user can access the secret by providing the valid fingerprint. We modify the fuzzy vault to protect fingerprint templates and to perform fingerprint verification with the protected template at the same time. This is challenging because the fingerprint verification is performed in the domain of the protected form. Based on the experimental results, we confirm that the proposed approach can perform the fingerprint verification with the protected template.

• Journal of Computing Science and Engineering
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• v.4 no.4
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• pp.291-312
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• 2010

The last decades a large amount of research has been done in the genomics domain which has and is generating terabytes, if not exabytes, of information stored globally in a very fragmented way. Different databases use different ways of storing the same data, resulting in undesired redundancy and restrained information transfer. Adding to this, keeping the existing databases consistent and data integrity maintained is mainly left to human intervention which in turn is very costly, both in time and money as well as error prone. Identifying a fixed conceptual dictionary in the form of a conceptual model thus seems crucial. This paper presents an effort to integrate the mutational data from the established genomic data source HGMD into a conceptual model driven database HGDB, thereby providing useful lessons to improve the already existing conceptual model of the human genome.

• Smart Structures and Systems
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• v.20 no.2
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• pp.115-126
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• 2017

The modal identification of large civil structures such as bridges under the ambient vibrational conditions has been widely investigated during the past decade. Many operational modal analysis methods have been proposed and successfully used for identifying the dynamic characteristics of the constructed bridges in service. However, there is very limited research available on reliable criteria for the robustness of these identified modal parameters of the bridge structures. In this study, two time-domain operational modal analysis methods, the data-driven stochastic subspace identification (SSI-DATA) method and the covariance-driven stochastic subspace identification (SSI-COV) method, are employed to identify the modal parameters from field recorded ambient acceleration data. On the basis of the SSI-DATA method, the modal contribution indexes of all identified modes to the measured acceleration data are computed by using the Kalman filter, and their applicability to evaluate the robustness of identified modes is also investigated. Here, the benchmark problem, developed by Hong Kong Polytechnic University with field acceleration measurements under different excitation conditions of a cable-stayed bridge, is adopted to show the effectiveness of the proposed method. The results from the benchmark study show that the robustness of identified modes can be judged by using their modal contributions to the measured vibration data. A critical value of modal contribution index of 2% for a reliable identifiability of modal parameters is roughly suggested for the benchmark problem.

• Geophysics and Geophysical Exploration
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• v.7 no.1
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• pp.7-13
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• 2004

In this paper, we demonstrate that Common Mid-Point (CMP) cross-correlation gathers of multi-channel and multi-shot surface waves give accurate phase-velocity curves, and enable us to reconstruct two-dimensional (2D) velocity structures with high resolution. Data acquisition for CMP cross-correlation analysis is similar to acquisition for a 2D seismic reflection survey. Data processing seems similar to Common Depth-Point (CDP) analysis of 2D seismic reflection survey data, but differs in that the cross-correlation of the original waveform is calculated before making CMP gathers. Data processing in CMP cross-correlation analysis consists of the following four steps: First, cross-correlations are calculated for every pair of traces in each shot gather. Second, correlation traces having a common mid-point are gathered, and those traces that have equal spacing are stacked in the time domain. The resultant cross-correlation gathers resemble shot gathers and are referred to as CMP cross-correlation gathers. Third, a multi-channel analysis is applied to the CMP cross-correlation gathers for calculating phase velocities of surface waves. Finally, a 2D S-wave velocity profile is reconstructed through non-linear least squares inversion. Analyses of waveform data from numerical modelling and field observations indicate that the new method could greatly improve the accuracy and resolution of subsurface S-velocity structure, compared with conventional surface-wave methods.