• Journal of Environmental Impact Assessment
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• v.11 no.4
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• pp.231-238
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• 2002

In this study we classified sediment types of tidal flat using Landsat-5 images. This is for groping the method which can analyze correctly various kinds of sediment faces through satellite images. This work was performed by referencing ground truth of sediment faces which was investigated in the field. With this data we classified Landsat-5 image of 1997's to grope a most suitable classification method. As a result, in case of south Kanghwa island area, it was the optimum way to compound band 4, 5, 7 of Landsat-5 TM imagery. And, this work classified 3 kinds of sediment faces - M(mud), sM(sandy mud) and (g)M(slightly gravelly mud) - in land and mixed water area. It is anticipated that if this method is applied to a image of extremely lower sea level time, it can classify the sediment types of a broad tidal flat area. This is expected to be a beginning of estimating the effect of sediment faces to the change of the tidal flat ecosystem.

• 한국지구물리탐사학회:학술대회논문집
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• 1999.08a
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• pp.156-175
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• 1999

Recently the application of geophysical well logging to geotechnical site investigation is increasing, because the merit that geophysical logs provide the high resolution and in-situ physical properties in volumes of rock surrounding the borehole. Geophysical well logs are used to identify lithologic boundaries and fracture, to determine the physical properties of rock(i.e., density, velocity etc.), and to detect permeable fracture zones that could be conduits for ground water movement through the rocks. The principle of heat-pulse meter, the calibration of gamma-gamma logging, and principles and data processing of full waveform sonic logging are briefly reviewed, and the case studies of geophysical logs are discussed. Correlation between velocity by sonic logging and rock mass classification such as RMR(Rock Mass Rating) value is considered.

• Journal of Information Processing Systems
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• v.15 no.3
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• pp.645-654
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• 2019

The purpose of this study was to collect and analyze personal bio data and social network services (SNS) data, derive user preference and user life pattern, and propose intuitive and precise user modeling. This study not only tried to conduct eye tracking experiments using various smart devices to be the ground of the recommendation system considering the attribute of smart devices, but also derived classification preference by analyzing eye tracking data of collected bio data and SNS data. In addition, this study intended to combine and analyze preference of the common classification of the two types of data, derive final preference by each smart device, and based on user life pattern extracted from final preference and collected bio data (amount of activity, sleep), draw the similarity between users using Pearson correlation coefficient. Through derivation of preference considering the attribute of smart devices, it could be found that users would be influenced by smart devices. With user modeling using user behavior pattern, eye tracking, and user preference, this study tried to contribute to the research on the recommendation system that should precisely reflect user tendency.

• Structural Engineering and Mechanics
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• v.68 no.6
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• pp.691-700
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• 2018

Ground granulated blast furnace slag (GGBS) is a by product obtained from iron and steel industries, useful in the design and development of high quality cement paste/mortar and concrete. This paper investigates the applicability of relevance vector machine (RVM) based regression model to predict the compressive strength of various GGBS based concrete mixes. Compressive strength data for various GGBS based concrete mixes has been obtained by considering the effect of water binder ratio and steel fibres. RVM is a machine learning technique which employs Bayesian inference to obtain parsimonious solutions for regression and classification. The RVM is an extension of support vector machine which couples probabilistic classification and regression. RVM is established based on a Bayesian formulation of a linear model with an appropriate prior that results in a sparse representation. Compressive strength model has been developed by using MATLAB software for training and prediction. About 70% of the data has been used for development of RVM model and 30% of the data is used for validation. The predicted compressive strength for GGBS based concrete mixes is found to be in very good agreement with those of the corresponding experimental observations.

• Journal of the Earthquake Engineering Society of Korea
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• v.26 no.4
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• pp.173-180
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• 2022

Most of the drinking water dams managed by the local governments in Korea are earthfill dams, and these dams have almost no geotechnical property information necessary for seismic performance evaluation. Nevertheless, in the rough planning stage for improving seismic safety for these dams, it is necessary to classify their relative seismic hazard against earthquakes and conduct an additional ground investigation. The zero seismic failure probability curve is a curve suggested in this study in which the probability of failure due to an earthquake becomes '0' regardless of the geotechnical properties of the earthfill dam. By examining the method and procedure for calculating failure probability due to an earthquake suggested in previous researches, the zero seismic failure probability curves for an earthquake in 1,000-year and 2,400-year return periods in Korea were presented in the form of a hyperbola on the plane of the dam height versus freeboard ratio (ratio of freeboard to dam height), respectively. The distribution characteristics of the dam height and the freeboard ratio of 81 Korean earthfill dams were presented. The two proposed zero seismic failure probability curves are shown on the plane of the dam height versus freeboard ratio, and the relative seismic hazard of 81 dams can be classified into three groups using these curves as boundaries. This study presented the method of classifying the relative seismic hazard and the classification result.

• Journal of the Earthquake Engineering Society of Korea
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• v.8 no.4
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• pp.11-20
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• 2004

This paper suggests the site-dependent ductility factor which is a key component of response modification factor(R). To compute the ductility factor, a group of 1,860 ground motions recorded from 47 earthquake was considered. Based on the local site conditions at the recording station, ground motions were classified into four groups according to average shear wave velocity. This site classification was consistent with site categories of the UBC(1997), NEHRP(1997) and IBC 2000(1997). Based on the results of regression analysis, a simplified equations were proposed to compute site-dependent ductility factors. The proposed equations were relatively simple and provide a good estimation of mean ductility factors. Based on the proposed equation, ductility factors considering the site conditions can be evaluated in accordance with the present building codes.

• Proceedings of the KIEE Conference
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• 2006.11a
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• pp.354-356
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• 2006

This paper presents a new one-terminal numerical algorithm for fault location estimation and for faults recognition. The proposed algorithm are derived for the case of most frequent single-phase line to ground fault in the time domain. The arc voltage wave shape is modeled numerically on the basis of a great number of arc voltage records obtained by transient recorder. From the calculated arc voltage amplitude it can make a decision whether the fault is permanent of transient. In this paper the algorithm uses a very short data window and enables fast fault detection and classification for real-time transmission line protection. To test the validity of the proposed algorithm the Electro-Magnetic Transient Program(EMTP/ATP) is used.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.21 no.6
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• pp.111-116
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• 2021

The hyper-spectral image is data obtained by dividing the electromagnetic wave band in the infrared region into hundreds of wavelengths. It is used to find or classify objects in various fields. Recently, deep learning classification method has been attracting attention. In order to use hyper-spectral image data as deep learning training data, a processing technique is required compared to conventional visible light image data. To solve this problem, we developed a software that selects specific wavelength images from the hyper-spectral data cube and performs the ground truth task. We also developed software to manage data including environmental information. This paper describes the configuration and function of the software.

• Advances in concrete construction
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• v.7 no.2
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• pp.65-74
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• 2019

This paper reports on the results of a parametric study, which examines the effects of varying aspect ratios on the dynamic response of cylindrical silos directly supported on the ground under earthquake loading. Previous research has shown that numerical models can provide considerably realistic simulations when it comes to the behavior of silos by using correct boundary conditions, appropriate element types and material models. To this end, a three dimensional numerical model, taking into account the bulk material-silo wall interaction, was produced by the ANSYS commercial program, which is in turn based on the finite element method. The results obtained from the numerical analysis are discussed comparatively in terms of dynamic material pressure, horizontal displacement, equivalent base shear force and equivalent bending moment responses for considered aspect ratios. The effects experienced because of the slenderness of the silo in regards to the seismic response were evaluated along with the effectiveness of the classification system proposed by Eurocode in evaluating the loads on the vertical walls. Results clearly show that slenderness directly affects the seismic response of such structures especially in terms of behavior and the magnitude of the responses. Furthermore the aspect ratio value of 2.0, given as a behavioral changing limit in the technical literature, can be used as a valid limit for seismic behavior.

• Journal of Platform Technology
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• v.10 no.4
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• pp.56-61
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• 2022

Various convergence technologies discovered through the 4th industrial revolution are permeating the industry. Drones are being used in industries such as construction, transportation, and national defense based on convergence technology. Quart-copter drone control is being used in a wide range of fields from the visual field of operation with the naked eye to the remote field of view using GCS. If we classify those who operate industrial drones, there are general pilots who directly use drones, instructors who train drone pilots, and mechanics who check the status of drones and use them for a long time. Depending on the shape of the screen of the drone GCS, a user's quick response or key data can be acquired. Accordingly, in this study, GUI characteristics were analyzed for the mission planner GCS and a screen composition method according to the user was proposed.