• Proceedings of the Korean Society for Agricultural Machinery Conference
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• 1996.06c
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• pp.171-190
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• 1996

Quality evaluation of agricultural products has been a subject of interest to many researches for many years. As a results, several nondestructive techniques for quality evaluation of agricultural products have been developed. These methods are based on the detection of various physical properties that correlate well with certain quality factors of the products. This paper presents an overview of various quality evaluation techniques that are based on one of the following properties : density, firmness , vibration characteristic , X-ray and gamma ray transmission, optical reflectance and transmission , electrical properties, aromatic volatile emission, and nuclear magnetic resonance (NMR). The sophistication of nondestructive methods has evolved rapidly with modern technologies. The use of various modern image acquisition techniques, such as solid state TV camera, line-scan camera, X-ray scanning , ultrasonic scanning and NMR imaging, in conjunction with image-processing te hniques has provided new opportunities for researchers to develop many new and improved techniques for nondestructive quality evaluation of agricultural products.

• Geomechanics and Engineering
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• v.17 no.6
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• pp.597-606
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• 2019

Ultrasonic Time-of-Flight Diffraction (TOFD) techniques are useful methods for non-destructive evaluation of fracture characteristics. This study focuses on the reliability and accuracy of ultrasonic diffraction methods to estimate the depth of rock fractures. The study material includes three different rock types; andesite, basalt and ignimbrite. Four different ultrasonic techniques were performed on these intact rocks. Artificial near-surface fracture depths were created in the laboratory by sawing. The reliability and accuracy of each technique was assessed by comparison of the repeated measurements at different path lengths along the rock surface. The standard error associated with the predictive equations is very small and their reliability and accuracy seem to be high enough to be utilized in estimating the depth of rock fractures. The performances of these techniques were re-evaluated after filling the artificial fractures with another material to simulate natural infills.

• Earthquakes and Structures
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• v.22 no.5
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• pp.487-502
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• 2022

China is prone to earthquake disasters, and the higher seismic performance is required by many existing civil buildings. And seismic evaluation and retrofit are effective measures to mitigate seismic hazards. With the development of performance-based seismic design and diverse retrofit technology for buildings, advanced evaluation methods and retrofit strategies are in need. In this paper, we introduced the evolution of seismic performance objectives in China combined with performance-based seismic design. Accordingly, multi-phase evaluation methods and comprehensive seismic capacity assessment are introduced. For buildings with seismic deficiency or higher performance requirements, the retrofit technologies are categorized into three types: component strengthening, system optimization, and passive control. Both engineering property and social property for the retrofit methods are discussed. The traditional seismic retrofit methods usually are costly and disturbing, and for example in Beijing, seismic strengthening costs approx. 1000 RMB/m² (for 160 USD/m²), for hospital building even more expensive as 5000 RMB/m²(for 790 USD/m²). So cost-efficient and little disturbance methods are promising techniques. In the end, some opinions about the retrofit strategy and schemes category are shared and wish to discuss the situation and future of seismic retrofit in China.

• Knowledge Management Research
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• v.20 no.2
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• pp.1-24
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• 2019

This tutorial introduces procedures and methods for performing structural equation modeling using R. To do this, we present advanced analysis methods based on structural equation model such as mediation effect analysis, moderation effect analysis, moderated mediation effect analysis, and multiple-group analysis with R program code using R lavaan package that supports structural equation modeling. R is flexible and scalable, unlike traditional commercial statistical packages. Therefore, new analytical techniques are likely to be implemented ahead of any other statistical package. From this point of view, R will be a very appropriate choice for applying new analytical techniques or advanced techniques that researchers need. Considering that various studies in the social sciences are applying structural equations modeling techniques and increasing interest in open source R, this tutorial is expected to be useful for researchers who are looking for alternatives to existing commercial statistical packages.

• Communications for Statistical Applications and Methods
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• v.24 no.6
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• pp.543-559
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• 2017

Tree-based regression and classification ensembles form a standard part of the data-science toolkit. Many commonly used methods take an algorithmic view, proposing greedy methods for constructing decision trees; examples include the classification and regression trees algorithm, boosted decision trees, and random forests. Recent history has seen a surge of interest in Bayesian techniques for constructing decision tree ensembles, with these methods frequently outperforming their algorithmic counterparts. The goal of this article is to survey the landscape surrounding Bayesian decision tree methods, and to discuss recent modeling and computational developments. We provide connections between Bayesian tree-based methods and existing machine learning techniques, and outline several recent theoretical developments establishing frequentist consistency and rates of convergence for the posterior distribution. The methodology we present is applicable for a wide variety of statistical tasks including regression, classification, modeling of count data, and many others. We illustrate the methodology on both simulated and real datasets.

• Proceedings of the Korea Water Resources Association Conference
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• 2018.05a
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• pp.150-150
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• 2018

The Numerical Weather Prediction (NWP) models provide information for weather forecasts. The highly nonlinear and complex interactions in the atmosphere are simplified in meteorological models through approximations and parameterization. Therefore, the simplifications may lead to biases and errors in model results. Although the models have improved over time, the biased outputs of these models are still a matter of concern in meteorological and hydrological studies. Thus, bias removal is an essential step prior to using outputs of atmospheric models. The main idea of statistical bias correction methods is to develop a statistical relationship between modeled and observed variables over the same historical period. The Model Output Statistics (MOS) would be desirable to better match the real time forecast data with observation records. Statistical post-processing methods relate model outputs to the observed values at the sites of interest. In this study three methods are used to remove the possible biases of the real-time outputs of the Weather Research and Forecast (WRF) model in Imjin basin (North and South Korea). The post-processing techniques include the Linear Regression (LR), Linear Scaling (LS) and Power Scaling (PS) methods. The MOS techniques used in this study include three main steps: preprocessing of the historical data in training set, development of the equations, and application of the equations for the validation set. The expected results show the accuracy improvement of the real-time forecast data before and after bias correction. The comparison of the different methods will clarify the best method for the purpose of the forecast skill enhancement in a real-time case study.

• Journal of the Korean Society of Visualization
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• v.8 no.3
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• pp.12-21
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• 2010

Swirling flows are found in very wide range of applications, for examples, cyclone separators, spraying machines, heat exchangers and jet pumps, ect. Relatively, little work has been done on the swirl flow using flow visualization techniques. This study deals with many visualization techniques to study on swirling flow. These techniques are related to oil films methods, smoke, dye liquids, liquid crystal, stroboscope light, smoke wire, white light, naphthalene sublimation, LDV(lase doppler Velocimetry) and PIV(particle image velocimetry). The present work has handled single, annular, carved tube, swirl expansion and swirl wake using several visualization methods in the vertical and horizontal circular tube.

• Journal of Computing Science and Engineering
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• v.2 no.2
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• pp.137-160
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• 2008

The increasing availability of personal location data pushed by the widespread use of location-sensing technologies raises concerns with respect to the safeguard of location privacy. To address such concerns location privacy-preserving techniques are being investigated. An important area of application for such techniques is represented by Location Based Services (LBS). Many privacy-preserving techniques designed for LBS are based on the idea of forwarding to the LBS provider obfuscated locations, namely position information at low spatial resolution, in place of actual users' positions. Obfuscation techniques are generally based on the use of geometric methods. In this paper, we argue that such methods can lead to the disclosure of sensitive location information and thus to privacy leaks. We thus propose a novel method which takes into account the semantic context in which users are located. The original contribution of the paper is the introduction of a comprehensive framework consisting of a semantic-aware obfuscation model, a novel algorithm for the generation of obfuscated spaces for which we report results from an experimental evaluation and reference architecture.

• Smart Structures and Systems
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• v.4 no.4
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• pp.465-492
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• 2008

Proper pretest planning is a vital component of any successful vibration test on engineering structures. The most important issue in dynamic testing of many engineering structures is arriving at the number and optimal placement of sensors. The sensors must be placed on the structure in such a way that all the important dynamic behaviour of a structural system is captured during the course of the test with sufficient accuracy so that the information can be effectively utilised for structural parameter identification or health monitoring. Several optimal sensor placement (OSP) techniques are proposed in the literature and each of these methods have been evaluated with respect to a specific problem encountered in various engineering disciplines like aerospace, civil, mechanical engineering, etc. In the present work, we propose to perform a detailed characteristic evaluation of some selective popular OSP techniques with respect to their application to practical civil engineering problems. Numerical experiments carried out in the paper on various practical civil engineering structures indicate that effective independence (EFI) method is more consistent when compared to all other sensor placement techniques.

• Korea-Australia Rheology Journal
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• v.18 no.1
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• pp.15-24
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• 2006

The first international inter-laboratory study, involving six laboratories, has been conducted to examine issues associated with yield stress measurements in suspensions. The initial focus of the project was to evaluate the reliability and reproducibility of several common yield stress measuring techniques employed in different laboratories and with different instruments. Aqueous suspensions of colloidal $TiO_2$ at concentrations of 40-70 wt% solids were used as the test fluids. A wide range of instruments and techniques employing both direct and indirect methods were used to determine the yield stress of the samples prepared according to a prescribed procedure. The results obtained indicated that although variations of results existed among different techniques, direct yield stress measurements using static methods produced more reliable and repeatable results than other methods. Variability of the yield stress measured using different techniques within any laboratory however was less significant than variability of the results among different laboratories. The nature and condition of the test suspensions was identified as the most likely factor responsible for the poor reproducibility of yield stress measurements from different laboratories.