• Proceedings of the Korea Water Resources Association Conference
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• 2009.05a
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• pp.2179-2183
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• 2009

As urbanization is progressed, the network for distributing water in a basin become complex due to the spatial expansion and parameter uncertainties of water supply systems. When a long range water supply plan is determined, the total construction and operation cost has to be evaluated with the system components and parameter uncertainties as many as possible. In this paper, the robust optimization approach of Bertsimas and Sim is applied in a hypothetical system to find a solution which remains feasible under the possible parameter uncertainties having the correlation effect between the uncertain coefficients. The system components to supply, treatment, and transport water are included in the developed water supply system and construction and expansion of the system is allowed for a long-range period. In this approach, the tradeoff between system robustness and total cost of the system is evaluated in terms of the degree of conservatism which can be converted to the probability of constraint violation. As a result, the degree of conservatism increases, the total cost is increased due to the installation of large capacity of treatment and transportation systems. The applied robust optimization technique can be used to determine a long-range water supply plan with the consideration of system failure.

• Computers and Concrete
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• v.18 no.5
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• pp.983-998
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• 2016

Structural optimization is one of the most important topics in structural engineering and has a wide range of applicability. Therefore, the main objective of the present study is to apply the Lagrange Multiplier Method (LMM) for minimum cost design of singly and doubly reinforced rectangular concrete beams. Concrete and steel material costs are used as objective cost function to be minimized in this study, and ultimate flexural strength of the beam is considered to be as the main constraint. The ultimate limit state method with partial material strength factors and equivalent concrete stress block is used to derive general relations for flexural strength of RC beam and empirical coefficients are taken from topic 9 of the Iranian National Building Regulation (INBR9). Optimum designs are obtained by using the LMM and are presented in closed form solutions. Graphical representation of solutions are presented and it is shown that proposed design curves can be used for minimum cost design of the beams without prior knowledge of optimization and without the need for iterative trials. The applicability of the proposed relations and curves are demonstrated through two real life examples of SRB and DRB design situations and it is shown that the minimum cost design is actually reached using proposed method.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.36S no.11
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• pp.44-53
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• 1999

This paper proposes an algorithm that postprocesses wavelet-compressed images by using regularized iterative image restoration. First, an appropriate modeling the image degradation system for wavelet-compression system is needed. Then, the method which uses one of nonlinear functions as constraint in regularized iterative restoration is proposed in order to remove coding artifacts efficiently, such as ringing artifact and blocking artifact, resulted from loss of high frequency coefficients. Lastly, experimental results show superiority of proposed algorithm as compared with existing algorithm.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.7
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• pp.3194-3216
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• 2018

Slow Feature Discriminant Analysis (SFDA) is a supervised feature extraction method inspired by biological mechanism. In this paper, a novel method called Two Dimensional Slow Feature Discriminant Analysis via $L_{2,1}$ norm minimization ($2DSFDA-L_{2,1}$) is proposed. $2DSFDA-L_{2,1}$ integrates $L_{2,1}$ norm regularization and 2D statically uncorrelated constraint to extract discriminant feature. First, $L_{2,1}$ norm regularization can promote the projection matrix row-sparsity, which makes the feature selection and subspace learning simultaneously. Second, uncorrelated features of minimum redundancy are effective for classification. We define 2D statistically uncorrelated model that each row (or column) are independent. Third, we provide a feasible solution by transforming the proposed $L_{2,1}$ nonlinear model into a linear regression type. Additionally, $2DSFDA-L_{2,1}$ is extended to a bilateral projection version called $BSFDA-L_{2,1}$. The advantage of $BSFDA-L_{2,1}$ is that an image can be represented with much less coefficients. Experimental results on three face databases demonstrate that the proposed $2DSFDA-L_{2,1}/BSFDA-L_{2,1}$ can obtain competitive performance.

• Journal of Institute of Control, Robotics and Systems
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• v.15 no.1
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• pp.99-104
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• 2009

This article describes the analysis of stable grasping for multi-fingered robot. An analysis method of stable grasping, which is based on the three-dimensional acceleration convex polytope, is proposed. This method is derived from combining dynamic equations governing object motion and robot motion, force relationship and acceleration relationship between robot fingers and object's gravity center through contact condition, and constraint equations for satisfying no-slip conditions at every contact points. After mapping no-slip condition to torque space, we derived intersected region of given torque bounds and the mapped region in torque space so that the intersected region in torque space guarantees no excessive torque as well as no-slip at the contact points. The intersected region in torque space is mapped to an acceleration convex polytope corresponding to the maximum acceleration boundaries which can be exerted by the robot fingers under the given individual bounds of each joints torque and without causing slip at the contacts. As will be shown through the analysis and examples, the stable grasping depends on the joint driving torque limits, the posture and the mass of robot fingers, the configuration and the mass of an object, the grasp position, the friction coefficients between the object surface and finger end-effectors.

• Nuclear Engineering and Technology
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• v.54 no.3
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• pp.803-810
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• 2022

The small modular liquid-metal fast reactor (SMFR) is an important component of advanced nuclear systems. SMFRs exhibit relatively low breeding capability and constraint space for control rod installation. Consequently, control rods are deeply inserted at beginning and are withdrawn gradually to compensate for large burnup reactivity loss in a long lifetime. This paper is committed to investigating the impact of control rod compensation operation on core neutronics characteristics. This paper presents a whole core fine depletion model of long lifetime SMFR using OpenMC and the influence of depletion chains is verified. Three control rod position schemes to simulate the compensation process are compared. The results show that the fine simulation of the control rod compensation process impacts significantly the fuel burnup distribution and absorber consumption. A control rod equivalent position scheme proposed in this work is an optimal option in the trade-off between computation time and accuracy. The control position is crucial for accurate power distribution and void feedback coefficients in SMFRs. The results in this paper also show that the pin level power distribution is important due to the heterogeneous distribution in SMFRs. The fuel burnup distribution at the end of core life impacts the worth of control rods.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.39 no.5
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• pp.11-20
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• 2002

Based on regularization principles, we propose a new dequantization scheme on DCT-based transform coding for reducing of blocking artifacts and minimizing the quantization error. The conventional image dequantization is simply to multiply the received quantized DCT coefficients by the quantization matrix. Therefore, for each DCT coefficients, we premise that the quantization noise is as large as half quantizer step size (in DCT domain). Our approach is based on basic constraint that quantization error is bounded to ${\pm}$(quantizer spacing/2) and at least there are not high frequency components corresponding to discontinuities across block boundaries of the images. Through regularization, our proposed dequantization scheme, sharply reduces blocking artifacts in decoded images. Our proposed algorithm guarantees that the dequantization process will map the quantized DCT coefficients will be evaluated against the standard JPEG, MPEG-1 and H.263 (with Annex J deblocking filter) decoding process. The experimental results will show visual improvements as well as numerical improvements in terms of the peak-signal-to-noise ratio (PSNR) and the blockiness measure (BM) to be defined.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.24 no.9B
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• pp.1742-1754
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• 1999

In this paper, we propose a rate control scheme, using histogram based rate-distortion (R-D) estimation, which produces a consistent picture quality between consecutive frames. The histogram based R-D estimation used in our rate control scheme offers a closed-form mathematical model that enable us to predict the bits and the distortion generated from an encoded frame at a given quantization parameter (QP) and vice versa. The most attractive feature of the R-D estimation is low complexity of computing the R-D data because its major operation is just to obtain a histogram or weighted histogram of DCT coefficients from an input picture. Furthermore, it is accurate enough to be applied to the practical video coding. Therefore, the proposed rate control scheme using this R-D estimation model is appropriate for the applications requiring low delay and low complexity, and controls the output bit-rate ad quality accurately. Our rate control scheme ensures that the video buffer do not underflow and overflow by satisfying the buffer constraint and, additionally, prevents quality difference between consecutive frames from exceeding certain level by adopting the distortion constraint. In addition, a consistent considering the maximum tolerance BER of the voice service. Also in Rician fading channel of K=6 and K=10, considering CLP=$10^{-3}$ as a criterion, it is observed that the performance improment of about 3.5 dB and 1.5 dB is obtained, respectively, in terms of $E_b$/$N_o$ by employing the concatenated FEC code with pilot symbols.

• International Journal of Highway Engineering
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• v.10 no.1
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• pp.117-122
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• 2008

Quality control of the concrete pavement in the early stage of curing is very important because it has a conclusive effect on its life span. Therefore, examining and analyzing the initial behavior of concrete pavement must precede an alternative to control its initial behavior. There are largely two influential factors for the initial behavior of concrete pavement. One is the drying shrinkage, and the other is the heat generated by hydration and thermal change inside the pavement depending on the change in the atmospheric temperature. Thus, the coefficient of thermal expansion and drying shrinkage can be regarded as very important influential factors for the initial behavior of the concrete. It has been a general practice up until now to measure the coefficient of thermal expansion from completely cured concrete. This practice has an inherent limitation in that it does not give us the coefficient of thermal expansion at the initial stage of curing. Additionally, it has been difficult to obtain the measurement of drying shrinkage due to the time constraint. This research examined and analyzed the early drying shrinkage of the concrete and measurements of the thermal expansion coefficients to formulate a plan to control its initial behavior. Additionally, data values for the variables of influence were collected to develop a prediction model for the initial behavior of the concrete pavement and the verification of the proposed model. In this research, thermal expansion coefficients of the concrete in the initial stage of curing ranged between $8.9{\sim}10.8{\times}10^{-6}/^{\circ}C$ Furthermore, the effects of the size and depth of the concrete on the drying shrinkage were analyzed and confirmed.

• Journal of Distribution Science
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• v.17 no.3
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• pp.85-95
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• 2019

Purpose - The existing marketing studies using Social Network Analysis have assumed that network structure variables are time-invariant. However, a node's network position can fluctuate considerably over time and the node's network structure can be changed dynamically. Hence, if such a dynamic structural network characteristics are not specified for virtual goods purchase model, estimated parameters can be biased. In this paper, by comparing a time-invariant network structure specification model(base model) and time-varying network specification model(proposed model), the authors intend to prove whether the proposed model is superior to the base model. In addition, the authors also intend to investigate whether coefficients of network structure variables are random over time. Research design, data, and methodology - The data of this study are obtained from a Korean social network provider. The authors construct a monthly panel data by calculating the raw data. To fit the panel data, the authors derive random effects panel tobit model and multi-level mixed effects model. Results - First, the proposed model is better than that of the base model in terms of performance. Second, except for constraint, multi-level mixed effects models with random coefficient of every network structure variable(in-degree, out-degree, in-closeness centrality, out-closeness centrality, clustering coefficient) perform better than not random coefficient specification model. Conclusion - The size and importance of virtual goods market has been dramatically increasing. Notwithstanding such a strategic importance of virtual goods, there is little research on social influential factors which impact the intention of virtual good purchase. Even studies which investigated social influence factors have assumed that social network structure variables are time-invariant. However, the authors show that network structure variables are time-variant and coefficients of network structure variables are random over time. Thus, virtual goods purchase model with dynamic network structure variables performs better than that with static network structure model. Hence, if marketing practitioners intend to use social influences to sell virtual goods in social media, they had better consider time-varying social influences of network members. In addition, this study can be also differentiated from other related researches using survey data in that this study deals with actual field data.