• Journal of the Korean GEO-environmental Society
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• v.12 no.9
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• pp.35-45
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• 2011

This paper is to analyze the behaviors of tunnel support by TDR(Time Domain Reflectometry) sensor using electrical pulse. To analysis the behaviors of tunnel support, Copper tape as sensing materials was studied for on-site installation. Copper tape to the top of the glass tape, foam tape, and shielding the lower part was used electromagnetic shield sheet. For a high sensitivity to load and fill out the measurement noise emissions has been developed for the production of materials. This sensing material through the tunnel model tests for the change by surcharge load in TDR data were analyzed. Varing stiffness and support of conditions were determined the change of TDR data through PVC pipe tunnel section model tests. By comparing TDR data and finite element analysis, the behaviors of the tunnel support materials were analyzed qualitatively.

• Journal of Internet Computing and Services
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• v.23 no.1
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• pp.87-93
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• 2022

Since 99% of PCs operating in the defense domain use the Windows operating system, detection and response of Window-based malware is very important to keep the defense cyberspace safe. This paper proposes a model capable of detecting malware in a Windows PE (Portable Executable) format. The detection model was designed with an emphasis on rapid update of the training model to efficiently cope with rapidly increasing malware rather than the detection accuracy. Therefore, in order to improve the training speed, the detection model was designed based on a Bidirectional LSTM (Long Short Term Memory) network that can detect malware with minimal sequence data without complicated pre-processing. The experiment was conducted using the EMBER2018 dataset, As a result of training the model with feature sets consisting of three type of sequence data(Byte-Entropy Histogram, Byte Histogram, and String Distribution), accuracy of 90.79% was achieved. Meanwhile, it was confirmed that the training time was shortened to 1/4 compared to the existing detection model, enabling rapid update of the detection model to respond to new types of malware on the surge.

• Journal of the Society of Naval Architects of Korea
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• v.60 no.2
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• pp.135-145
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• 2023

Developing high-fidelity Computational Fluid Dynamics (CFD) simulation methods used to evaluate the airwake characteristics along a flight deck of a large ship, the various kind of data such as actual ship measurement and wind tunnel results are required to verify the accuracy of CFD simulation. Inflow velocity profile at the bow, local unsteady flow field data around the flight deck, and highly reliable wind tunnel data which were measured after reviewing Atmospheric Boundary Layer (ABL) simulation and Reynolds Number effects were also used to determine the key parameters such as turbulence model, time resolution and accuracy, grid resolution and type, inflow condition, domain size, simulation length, and so on in STAR CCM⁺. Velocity ratio and turbulent intensity difference between Full-scale CFD and actual ship measurement at the measurement points show less than 2% and 1.7% respectively. And differences in velocity ratio and turbulence intensity between wind tunnel test and small-scale CFD are both less than 2.2%. Based upon this fact, the selected parameters in CFD simulation are highly reliable for a specific wind condition.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.11
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• pp.1586-1591
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• 2022

Kirchhoff-Love plate (KLP) equation is a well established theory for a description of a deformation of a thin plate under certain outer source. Meanwhile, analysis of a vibrating plate in a frequency domain is important in terms of obtaining the main frequency/eigenfunctions and predicting the vibration of plate. Among various modal analysis methods, dynamic mode decomposition (DMD) is one of the efficient data-driven methods. In this work, we carry out DMD based modal analysis for KLP where thin plate is under effects of sine-type outer force. We first construct discrete time series of KLP solutions based on a finite difference method (FDM). Over 720,000 number of FDM-generated solutions, we select only 500 number of solutions for the DMD implementation. We report the resulting DMD-modes for KLP. Also, we show how DMD can be used to predict KLP solutions in an efficient way.

• International conference on construction engineering and project management
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• 2024.07a
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• pp.1256-1263
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• 2024

In the realm of Architecture, Engineering, and Construction (AEC) education, various factors play a crucial role in shaping students' acceptance of the learning environments facilitated by visualization technologies, such as virtual reality (VR). Works on leveraging the heterogeneous educational information (i.e., pedagogical data, student performance data, and student survey data) to identify essential factors influencing students' learning experience and performance in virtual environments are still insufficient. This research proposed KnowLearn, an interactive learning assistant system, to integrate an educational knowledge graph (KG) and a locally deployed large language model (LLM) to generate real-time personalized learning recommendations. As the knowledge base of KnowLearn, the educational KG accommodated multi-faceted educational information from twelve perspectives, such as the teaching content, students' academic performance, and their perceived confidence in a specific course from the AEC discipline. A heterogeneous graph attention network (HAN) was utilized to infer the latent information in the KG and, thus, identified the perceived confidence, intention to use, and performance in a relevant quiz as the top three indicators that significantly influenced students' learning outcomes. Based on the information preserved in the KG and learned from the HAN model, the LLM enhanced the personalization of recommendations concerning adopting virtual learning environments while protecting students' privacy. The proposed KnowLearn system is expected to feasibly provide enhanced recommendations on the teaching module design for educators from the AEC domain.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.6
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• pp.46-54
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• 2018

The Internet of Things (IoT) is an environment in which various devices provide services to users through communications. Because of the nature of the IoT, data are stored and distributed in heterogeneous information systems. In this situation, IoT end applications should be able to access data without having information on where the data are or what the type of storage is. This mechanism is called Service Discovery (SD). However, some problems arise, since the current SD architectures search for data in physical devices. First, turnaround time increases from searching for services based on physical location. Second, there is a need for a data structure to manage devices and services separately. These increase the administrator's service configuration complexity. As a result, the device-oriented SD structure is not suitable to the IoT. Therefore, we propose an SD structure called Name-based Service-centric Service Discovery (NSSD). NSSD provides name-based centralized SD and uses the IoT edge gateway as a cache server to speed up service discovery. Simulation results show that NSSD provides about twice the improvement in average turnaround time, compared to existing domain name system and distributed hash table SD architectures.

• The Bulletin of The Korean Astronomical Society
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• v.40 no.1
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• pp.52.1-52.1
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• 2015

We have recently installed SQUEAN on the 82 inch telescope at the McDonald Observatory, USA. This instrument consists of an ANDOR CCD camera, a focal reducer, an electronic box, an auto guiding system and a new filter wheel which holds up to 20 filters. Currently the filter wheel is equipped with Johnson-Cousins BVRI filters, SDSS rizY and isiz filters, and 50nm medium band pass filters (M625(625nm), M675(675nm), M725(725nm), M775(775nm), M825(825nm), M875(875nm), M925s(925nm), M975(975nm), and M1025(1025nm)). Our medium band pass filter system is suitable with SED fitting. Filter transformation methods are essential for time-domain observations including transient objects, e.g., supernovae, variable stars, and solar system bodies. In this work, we develop a series of equations to convert the open clusters photometry data within these filter systems.

• Journal of the Korean GEO-environmental Society
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• v.13 no.12
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• pp.17-25
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• 2012

In this study, dielectrical constant of the ground was measured using TDR method and correlated with water contents and density of ground. In order to evaluate the applicability as a cavity exploration, model experiments were carried out to analyze the effects of cavity size on the dielectrical constant. Test result indicated that dielectrical constant of the ground tended to linearly increase with the increase in water contents and density, which can be represented in a certain relational expression. Also, the dielectrical constant of ground varied sensitively with the cavity size of ground. The results conclude that the dielectrical constant, water contents and density of the ground proved to have a correlation among them, and the dielectrical constant is expected to be a basic data on cavity exploration.

• Smart Structures and Systems
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• v.12 no.1
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• pp.23-39
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• 2013

In this article, a smart multifunctional optical system-on-a-chip (SOC) sensor platform is presented and its application for fiber Bragg grating (FBG) sensor interrogation in optical sensor networks is investigated. The smart SOC sensor platform consists of a superluminescent diode as a broadband source, a tunable microelectromechanical system (MEMS) based Fabry-P$\acute{e}$rot filter, photodetectors, and an integrated microcontroller for data acquisition, processing, and communication. Integrated with a wireless sensor network (WSN) module in a compact package, a smart optical sensor node is developed. The smart multifunctional sensor platform has the capability of interrogating different types of optical fiber sensors, including Fabry-P$\acute{e}$rot sensors and Bragg grating sensors. As a case study, the smart optical sensor platform is demonstrated to interrogate multiplexed FBG strain sensors. A time domain signal processing method is used to obtain the Bragg wavelength shift of two FBG strain sensors through sweeping the MEMS tunable Fabry-P$\acute{e}$rot filter. A tuning range of 46 nm and a tuning speed of 10 Hz are achieved. The smart optical sensor platform will open doors to many applications that require high performance optical WSNs.

• Structural Engineering and Mechanics
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• v.63 no.6
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• pp.779-788
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• 2017

System identification and damage detection for structural health monitoring have received considerable attention. Various time domain analysis methodologies based on measured vibration data of structures have been proposed. Among them, recursive least-squares estimation of structural parameters which is also known as parametric Kalman filter (PKF) approach has been studied. However, the conventional PKF requires that all the external excitations (inputs) be available. On the other hand, structural uncertainties are inevitable for civil infrastructures, it is necessary to develop approaches for probabilistic damage detection of structures. In this paper, a parametric Kalman filter with unknown inputs (PKF-UI) is proposed for the simultaneous identification of structural parameters and the unmeasured external inputs. Analytical recursive formulations of the proposed PKF-UI are derived based on the conventional PKF. Two scenarios of linear observation equations and nonlinear observation equations are discussed, respectively. Such a straightforward derivation of PKF-UI is not available in the literature. Then, the proposed PKF-UI is utilized for probabilistic damage detection of structures by considering the uncertainties of structural parameters. Structural damage index and the damage probability are derived from the statistical values of the identified structural parameters of intact and damaged structure. Some numerical examples are used to validate the proposed method.