• Steel and Composite Structures
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• v.49 no.1
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• pp.65-79
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• 2023

This paper presents a development of empirical evaluations, which can be used to evaluate the damage of fiber-reinforced concrete composites (FRC) wall subjected to close-in blast loads. For this development, a combined application of numerical simulation and machine learning approaches are employed. First, finite element modeling of FRC wall under blast loading is developed and verified using experimental data. Numerical analyses are then carried out to investigate the dynamic behavior of the FRC wall under blast loading. In addition, a data set of 384 samples on the damage of FRC wall due to blast loads is then produced in order to develop machine learning models. Second, three robust machine learning models of Random Forest (RF), Support Vector Machine (SVM), and Extreme Gradient Boosting (XGBoost) are employed to propose empirical evaluations for predicting the damage of FRC wall. The proposed empirical evaluations are very useful for practical evaluation and design of FRC wall subjected to blast loads.

• Journal of The Korean Association For Science Education
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• v.36 no.4
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• pp.551-561
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• 2016

The purpose of this study is to investigate both theoretically and empirically the roles of models in abductive reasoning for scientific problem solving. The context of the study is design-based research the goal of which is to develop inquiry learning programs in the domain of earth science, and the current article dealt with an early process of redesigning an abductive inquiry activity in geology. In the theoretical study, an extensive review was conducted with the literature addressing abduction and modeling together as research methods characterizing earth science. The result led to a tentative scheme for modeling-based abductive inference, which represented relationships among evidence, resource models, and explanatory models. This scheme was improved by the empirical study in which experts' reasoning for solving a geological problem was analyzed. The new scheme included the roles of critical evidence, critical resource models, and a scientifically sound explanatory model. Pedagogical implications for the support of student reasoning in modeling-based abductive inquiry in earth science was discussed.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2007.11a
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• pp.1386-1390
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• 2007

This paper presents the equipment condition monitoring technology for the process or the equipment using statistical techniques. The equipment condition monitoring system consists of an empirical model to estimate the expected sensor values of process variables and a diagnose model to detect the abnormal condition and to identify the root source of the problem. The empirical model is constructed by the analysis of historic data. The diagnose model uses the sequential probability ratio test (SPRT) technique. The monitoring system was tested with real operating data acquired from the Reactor Coolant Pump Seal in the Nuclear Power Plant. It can detect the system degradation or failure at the early stage since it is able to catch the subtle deviation of process variables from normal condition.

• Proceedings of the KSRS Conference
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• 1999.11a
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• pp.154-157
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• 1999

Microwave polarimetric backscattering from a wet soil surface had been measured using a Ku-band polarimetric scatterometer at the incidence angles ranging from 10$^{\circ}$ to 70$^{\circ}$ Since the accurate target parameters as well as the radar parameters are necessary for radar scattering modeling, a complete and accurate set of ground truth data were also collected, from which accurate measurements were made of the rms height, correlation length, and dielectric constant. The measured polarimetric backscattering coefficients (vv-, hh-, vh-, hv-polarizations) were compared with theoretical models and empirical models. A new semi-empirical model for microwave polarimetric radar backscattering from bare soil surfaces was developed using polarimetric radar measurements and the knowledge based on the theoretical and numerical solutions. The model was found to yield very good agreement with the backscattering measurements of this study.

• International Area Studies Review
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• v.20 no.3
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• pp.123-144
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• 2016

This paper investigates the linkages between returns both in foreign exchange and stock markets, and uncertainties in two markets using daily data for the period of 16 July 2004 to 30 June 2014 in Nepalese economy. Four hypotheses are tested about how uncertainty influences the stock index and exchange rates. From the empirical results, a bivariate EGARCH-M model is the best to explain the volatility in the two markets. There is a negative relationship from the exchange rates return to stock price return. Empirical results do provide strong empirical confirmation that negative effect of stock index uncertainty and positive effect of exchange rates uncertainty on average stock index. GARCH-in-mean variables in AR modeling are significant and shows that there is positive effect of exchange rates uncertainty and negative effect of stock index uncertainty on average exchange rates. Stock index shocks have longer lived effects on uncertainty in the stock market than exchange rates shock have on uncertainly in the foreign exchange market. The effect of the last period's shock, volatility is more sensitive to its own lagged values.

• Korea Trade Review
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• v.45 no.5
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• pp.201-222
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• 2020

This paper examines that determinants of BAOMAI, (i.e., behavior of Chinese tourist bulk purchase in duty free shop) with analytical framework and empirical tests. The results of applying the structural equation modeling to 196 samples suggest that Chinese tourist consumption orientations (conspicuous/compulsive/unplanned consumption) have a positive effect on BAOMAI decision value chain (perceived value and loyalty). The marketing mix of duty free shop as control variables in research framework also have a positive effect on BAOMAI perceived values (functional/social/emotional value). This paper has a contribution to prior literatures: the first empirical analysis on BAOMAI determinants with exploring scholarly definition.

• Asia pacific journal of information systems
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• v.28 no.2
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• pp.75-92
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• 2018

Conceptual modeling is well suited as a subject that constitutes the "core" of the Information Systems (IS) discipline and has grown in response to IS development. Several modeling grammars and methods have been studied extensively in the IS discipline. Previous studies, however, present deficiencies in research methods and even put forward contradictory results about the ternary relationship in conceptual modeling. For instance, some studies contend that the semantics of a binary relationship are better for novices, but others argue that a ternary relationship is better than three binary relationships when the association among three entity types clearly exists. The objective of this research is to acquire complete and accurate understanding of the ternary relationship, specifically to understand practitioners' modeling performance when utilizing either a ternary or binary relationship. To the best of our knowledge, no previous work clearly compares real-world modeler performance differences between binary and ternary representations. By investigating practitioners' understanding of ternary relationship and identifying practitioners' cognition, this research can broaden the perspective on conceptual modeling.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.8 no.4
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• pp.19-28
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• 1999

In order to control thermal deformation of the machine origin of machine tools a empirical model and a compensation system have been developed, Prior to empirical modeling the volumetric error considering shape errors and joint errors of slides is formulated through the homogeneous transformation matrix (HTM) and kinematic chain. Simulation results of the HTM method show that the thermal error of the machine origin is more critical than position-dependent errors. In order to make a stable and effective software error compensation system the GMDH (Group Method of Data Handling) models are constructed to estimate the thermal deformation of the machine origin by measuring deformation data and temperature data. A test bar and gap sensors are used to measure the deformation data. In order to compensate the estimated error the work origin shift method is developed by implementing a digital I/O interface board between a CNC controller and an IBM PC. The method shifts the work origin as much as the amounts which are calculated by the pre-established thermal error model. The experiment results for a vertical machining center show that the thermal deformation of the machine origin is reduced within $\pm$5$mu extrm{m}$.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.43 no.12 s.354
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• pp.33-39
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• 2006

An empirical nonlinear model with intrinsic nonlinear elements has been newly developed to predict the RF nonlinear characteristics of nano-scale bulk MOSFET accurately over the wide bias range. Using an extraction method suitable for nano-scale MOSFET, the bias-dependent data of intrinsic model parameters have been accurately obtained from measured S-parameters. The intrinsic nonlinear capacitance and drain current equations have been empirically obtained through 3-dimensional curve-fitting to their bias-dependent curves. The modeled S-parameters of 60nm MOSFET have good agreements with measured ones up to 20GHz in the wide bias range, verifying the accuracy of the nano-scale MOSFET model.

• Computers and Concrete
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• v.21 no.5
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• pp.593-605
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• 2018

A nonlinear finite element modeling approach is developed to assess the behavior of a dowel bar embedded on a single concrete block substrate, subjected to monotonic loading. In this approach, a discrete representation of the steel reinforcing bar is considered, using beam finite elements with nonlinear material behavior. The bar is connected to the concrete embedment through nonlinear Winkler spring elements. This modeling approach can only be used if a new constitutive model is developed for the spring elements, to simulate the deformability and strength of the concrete substrate. To define this constitutive model, an extensive literature review was conducted, as well as 3 experimental tests, in order to select the experimental data which can be used in the calibration of the model. Based on this data, an empirical model was established to predict the global dowel response, for a wide range of bar diameters and concrete strengths. This empirical model provided the information needed for calibration of the nonlinear Winkler spring model, valid for dowel displacements up to 4 mm. This new constitutive model is composed by 5 stages, in order to reproduce the concrete substrate response.