• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.11
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• pp.4557-4572
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• 2020

The Alaska competition provides an opportunity to study the practical problems of real-world steganalysis. Participants are required to solve steganalysis involving various embedding schemes, inconsistency JPEG Quality Factor and various processing pipelines. In this paper, we propose a method to ensemble multiple deep learning steganalyzers. We select SRNet and RESDET as our base models. Then we design a three-layers model ensemble network to fuse these base models and output the final prediction. By separating the three colors channels for base model training and feature replacement strategy instead of simply merging features, the performance of the model ensemble is greatly improved. The proposed method won second place in the Alaska 1 competition in the end.

• Management & Information Systems Review
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• v.29 no.2
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• pp.1-25
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• 2010

This study attempted to empirically test the determinants of stock returns in Korean stock market applying multi-factor model proposed by Haugen and Baker(1996). Regression models were developed using 16 variables related to liquidity, risk, historical price, price level, and profitability as independent variables and 690 stock monthly returns as dependent variable. For the statistical analysis, the data were collected from the Kis Value database and the tests of forecasting power in this study minimized various possible bias discussed in the literature as possible. The statistical results indicated that: 1) Liquidity, one-month excess return, three-month excess return, PER, ROE, and volatility of total return affect stock returns simultaneously. 2) Liquidity, one-month excess return, three-month excess return, six-month excess return, PSR, PBR, ROE, and EPS have an antecedent influence on stock returns. Meanwhile, realized returns of decile portfolios increase in proportion to predicted returns. This results supported previous study by Haugen and Baker(1996) and indicated that firm-characteristic model can better predict stock returns than CAPM. 3) The firm-characteristic model has better predictive power than Fama-French three-factor model, which indicates that a portfolio constructed based on this model can achieve excess return. This study found that expected return factor models are accurate, which is consistent with other countries' results. There exists a surprising degree of commonality in the factors that are most important in determining the expected returns among different stocks.

• Smart Structures and Systems
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• v.29 no.2
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• pp.321-336
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• 2022

Model uncertainty is a key factor that could influence the accuracy and reliability of numerical model-based analysis. It is necessary to acquire an appropriate updating approach which could search and determine the realistic model parameter values from measurements. In this paper, the Bayesian model updating theory combined with the transitional Markov chain Monte Carlo (TMCMC) method and K-means cluster analysis is utilized in the updating of the structural model parameters. Kriging and polynomial chaos expansion (PCE) are employed to generate surrogate models to reduce the computational burden in TMCMC. The selected updating approaches are applied to three structural examples with different complexity, including a two-storey frame, a ten-storey frame, and the national stadium model. These models stand for the low-dimensional linear model, the high-dimensional linear model, and the nonlinear model, respectively. The performances of updating in these three models are assessed in terms of the prediction uncertainty, numerical efforts, and prior information. This study also investigates the updating scenarios using the analytical approach and surrogate models. The uncertainty quantification in the Bayesian approach is further discussed to verify the validity and accuracy of the surrogate models. Finally, the advantages and limitations of the surrogate model-based updating approaches are discussed for different structural complexity. The possibility of utilizing the boosting algorithm as an ensemble learning method for improving the surrogate models is also presented.

• Culinary science and hospitality research
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• v.18 no.2
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• pp.82-90
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• 2012

This study was conducted to evaluate a take-out food safety perception instrument that could be used by foodservice establishments. A total of 324 responses was collected via online survey, and 299 responses (92.3%) were used for the statistical analysis. Data was randomly split into two groups. Exploratory Factor Analysis (EFA) was performed on the first split-half sample (n=150) to identify a factor structure using standard principal component analysis. EFA revealed three dimensions, titled "Consumer food safety perception," "Take-out food handling," and "Elements impacting on purchase decisions." Confirmatory Factor Analysis (CFA) was performed on the remaining half sample (n=149) using Structural Equation Modeling (SEM). CFA revealed acceptable absolute model fits for three dimensions and excellent comparative model fits for the instrument. These findings propose standardized measures that can be useful in assessing the take-out food safety perception.

• Steel and Composite Structures
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• v.18 no.6
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• pp.1465-1478
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• 2015

The effect of cutting off fibers on transient load in a polymeric matrix composite lamina was studied in this paper. The behavior of fibers was considered to be linear elastic and the matrix behavior was considered to be linear viscoelastic. To model the viscoelastic behavior of matrix, a three parameter solid model was employed. To conduct this research, finite difference method was used. The governing equations were obtained using Shear-lag theory and were solved using boundary and initial conditions before and after the development of break. Using finite difference method, the governing integro-differential equations were developed and normal stress in the fibers is obtained. Particular attention is paid the dynamic overshoot resulting when the fibers are suddenly broken. Results show that considering viscoelastic properties of matrix causes a decrease in dynamic load concentration factor and an increase in static load concentration factor. Also with increases the number of broken fibers, trend of increasing load concentration factor decreases gradually. Furthermore, the overshoot of load in fibers adjacent to the break in a polymeric matrix with high transient time is lower than a matrix with lower transient time, but the load concentration factor in the matrix with high transient time is lower.

• Computers and Concrete
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• v.19 no.5
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• pp.527-535
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• 2017

In this study, an aging deformation statistical model for a unique high and steep rock slope was proposed, and the aging characteristic of the slope deformation was better reflected. The slope displacement was affected by multiple-environmental factors in multiple scales and displayed the same tendency with a rising water level. The statistical model of the high and steep rock including non-aging factors was set up based on previous analyses and the study of the deformation and residual tendency. The rule and importance of the water level factor as a non-aging unit was analyzed. A partitioned statistical model and mutation model were established for the comprehensive cumulative displacement velocity with the monitoring study under multiple factors and multiple parameters. A spatial model was also developed to reflect and predict the whole and sectional deformation character by combining aging, deformation and space coordinates. A neural network model was built to fit and predict the deformation with a high degree of precision by mastering its feature of complexity and randomness. A three-dimensional finite element model of the slope was applied to approach the structure character using numerical simulations. Further, a three-dimensional finite element model of the slope and dam was developed, and the whole deformation state was analyzed. This study is expected to provide a powerful and systematic method to analyze very high, important and dangerous slopes.

• Proceedings of the KIPE Conference
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• 1998.10a
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• pp.630-635
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• 1998

This paper establishes in a new unified manner new mathematical models with core(iron) loss factor for two kinds of AC motors, induction and synchronous motors which are supposed to generate torque precisely or/and efficiently under vector controls. Our new models consist of three basic equations consistent with the others such as differential equation describing electromagnetic dynamics, torque equation describing torque generating mechanism, energy transmission equation describing how injected energy is wasted, saved or transmitted where all vector signals are defined in general frame of arbitrary instant angular velocity. It is clearly shown in our models that equivalent core-loss resistance can express appropriately and separately both eddy-current and hysteresis losses rather than mere vague loss. Proposed model of induction motor is the most compact in sense of the number of employed interior states and parameters. This compact model can also represent eddy-current and hysteresis losses of rotor as well as stator. For synchronous motor, saliency is taken into consideration. As well known model for cylindrical motor can be obtained directly from salient one as its special case.

• The KSFM Journal of Fluid Machinery
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• v.11 no.1
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• pp.52-60
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• 2008

Staggered dimples printed on opposite walls of an internal cooling channel are formulated numerically and optimized to enhance heat transfer performance. Nusselt number and friction factor based objectives are considered and a weighted average surrogate model is used to approximate the data generated by numerical simulation. The dimpled channel shape is defined by three geometric design variables, and the design point within design space are selected using Latin hypercube sampling. A weighted-sum method for multi-objective optimization is applied to integrate multiple objectives into a single objective. By the optimization, the objective function value is improved largely and heat transfer rate is increase much higher than pressure loss increase due to shape deformation. Channel with vertically non-symmetric optimum dimples is tested and found that the best appears if dimples on opposite wall are displaced by one quarter of dimple spacing.

• Journal of Applied Reliability
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• v.6 no.1
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• pp.37-50
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• 2006

The accelerated life tests of the catalytic gas sensor were performed at three different gas concentration conditions. From the test data, the power-Weibull model was estimated and the acceleration factor between test condition 25%LEL(Lowe Explosive Limit) and use condition 5%LEL was about 3 according to this acceleration model. Using this acceleration factor, life test specification for qualifying that B10 lifetime of the catalytic gas sensor meets the goal lifetime (5 years) was designed.

• Journal of the Korean Institute of Intelligent Systems
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• v.12 no.3
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• pp.255-260
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• 2002

This paper describes a fuzzy-based system for analyzing the stress intensity factors (SIFs) of three-dimensional (3D) cracks. A geometry model, i.e. a solid containing one or several 3D cracks is defined. Several distributions of local node density are chosen, and then automatically superposed on one another over the geometry model by using the fuzzy knowledge processing. Nodes are generated by the bucketing method, and ten-coded quadratic tetrahedral solid elements are generated by the Delaunay triangulation techniques. The singular elements such that the mid-point nodes near crack front are shifted at the quarter-points, and these are automatically placed along the 3D crack front. The complete finite element(FE) model is generated, and a stress analysis is performed. The SIFs are calculated using the displacement extrapolation method. To demonstrate practical performances of the present system, semi-elliptical surface cracks in a inhomogeneous plate subjected to uniform tension are solved.