• Journal of Korean Society of Water and Wastewater
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• v.34 no.5
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• pp.311-321
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• 2020

In this study, a model to optimize residual chlorine concentrations in a water supply system was developed using a multi-objective genetic algorithm. Moreover, to quantify the effects of optimized residual chlorine concentration management and to consider customer service requirements, this study developed indices to quantify the spatial and temporal distributions of residual chlorine concentration. Based on the results, the most economical operational method to manage booster chlorination was derived, which would supply water that satisfies the service level required by consumers, as well as the cost-effectiveness and operation requirements relevant to the service providers. A simulation model was then created based on an actual water supply system (i.e., the Multi-regional Water Supply W in Korea). Simulated optimizations were successful, evidencing that it is possible to meet the residual chlorine concentration demanded by consumers at a low cost.

• JSTS:Journal of Semiconductor Technology and Science
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• v.15 no.5
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• pp.437-444
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• 2015

In simulation-based circuit optimization, many simulation runs may be wasted while evaluating infeasible designs, i.e. the designs that do not meet the constraints. To avoid such a waste, this paper investigates the use of support vector machine (SVM) classifiers in predicting the design's feasibility prior to simulation and the optimal selection of the SVM parameters, namely, the Gaussian kernel shape parameter ${\gamma}$ and the misclassification penalty parameter C. These parameters affect the complexity as well as the accuracy of the model that SVM represents. For instance, the higher ${\gamma}$ is good for detailed modeling and the higher C is good for rejecting noise in the training set. However, our empirical study shows that a low ${\gamma}$ value is preferable due to the high spatial correlation among the circuit design candidates while C has negligible impacts due to the smooth and clean constraint boundaries of most circuit designs. The experimental results with an LC-tank oscillator example show that an optimal selection of these parameters can improve the prediction accuracy from 80 to 98% and model complexity by $10{\times}$.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.27 no.3
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• pp.381-386
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• 2003

Gradually engineering designers are determined based on computer simulations. Modeling of the computer simulation however is too expensive and time consuming in a complicate system. Thus, designers often use approximation models called metamodels, which represent approximately the relations between design and response variables. There arc general metamodels such as response surface model and kriging metamodel. Response surface model is easy to obtain and provides explicit function. but it is not suitable for highly nonlinear and large scaled problems. For complicate case, we may use kriging model that employs an interpolation scheme developed in the fields of spatial statistics and geostatistics. This class of into interpolating model has flexibility to model response data with multiple local extreme. In this study. metamodeling techniques are adopted to carry out the shape optimization of a funnel of Cathode Ray Tube. which finds the shape minimizing the local maximum principal stress Optimum designs using two metamodels are compared and proper metamodel is recommended based on this research.

• Proceeding of KASS Symposium
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• 2006.05a
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• pp.233-238
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• 2006

This paper provides a new topology optimization technique which is intended to maximize the fundamental frequency with simultaneous consideration of other natural frequencies in the form of multi-frequency problems. The modal strain energy is considered as the objective function to be minimized and the initial volume of structures is used as the constraint function. The resizing algorithm based on the optimality criteria is adopted to update the hole size existing inside the material. From numerical tests, the proposed technique is found to be very effective to maximize the fundamental frequency of the structure and it can also successfully consider several higher mode effects into the optimum topology of structure through the introduction of weights.

• Structural Engineering and Mechanics
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• v.48 no.3
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• pp.395-414
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• 2013

The present study fundamentally investigated the mechanical performance of the rib-stiffened super-wide bridge deck with twin box girders in concrete, which is a very popular application to efficiently widen the bridges with normal span. The shear lag effects of the specific cross-sections were firstly studied. The spatial stress distribution and local stiffness of the bridge deck with twin box girders were then investigated under several typical wheel load conditions. Meanwhile, a comparative study for the bridge deck with and without stiffening ribs was also carried out during the investigation; thereby, a design optimization for the stiffening ribs was further suggested. Finally, aiming at the preliminary design, an approximate methodology to manually calculate the bending moments of the rib-stiffened bridge deck was analytically proposed for engineers to quickly assess its performance. This rib-stiffened bridge deck with twin box girders can be widely applied for concrete (especially concrete cable-stayed) bridges with normal span, however, requiring a super-wide bridge width due to the traffic flow.

• Geomechanics and Engineering
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• v.34 no.1
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• pp.29-41
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• 2023

The 3D geospatial modeling of geotechnical information can aid in understanding the geotechnical characteristic values of the continuous subsurface at construction sites. In this study, a geostatistical optimization model for the three-dimensional (3D) mapping of subsurface stratification and the SPT-N value based on a trial-and-error rule was developed and applied to a dam emergency spillway site in South Korea. Geospatial database development for a geotechnical investigation, reconstitution of the target grid volume, and detection of outliers in the borehole dataset were implemented prior to the 3D modeling. For the site-specific subsurface stratification of the engineering geo-layer, we developed an integration method for the borehole and geophysical survey datasets based on the geostatistical optimization procedure of ordinary kriging and sequential Gaussian simulation (SGS) by comparing their cross-validation-based prediction residuals. We also developed an optimization technique based on SGS for estimating the 3D geometry of the SPT-N value. This method involves quantitatively testing the reliability of SGS and selecting the realizations with a high estimation accuracy. Boring tests were performed for validation, and the proposed method yielded more accurate prediction results and reproduced the spatial distribution of geotechnical information more effectively than the conventional geostatistical approach.

• Journal of the Korean Mathematical Society
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• v.38 no.3
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• pp.523-559
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• 2001

To predict the fate of groundwater contaminants, accurate spatially continuous information is needed. Because most field sampling of groundwater contaminants are not conducted spatially continuous manner, a special estimation technique is required to interpolate/extrapolate concentration distributions at unmeasured locations. A practical three-dimensional estimations method for in situ groundwater contaminant concentrations is introduced. It consistas of two general steps: estimation of macroscopic transport process and kriging. Using field data and nonlinear optimization techniques, the macroscopic behavior of the contaminant plume is estimated. A spatial distribution of residuals is obtained by subtracting the macroscopic transport portion from field data, then kriging is applied to estimate residuals at unsampled locations. To reduce outlier effects on obtaining correlations between residual data which are needed for determining variougram models, the R(sub)p-estimator is introduced. The proposed estimation method is applied to a field data set.

• IEIE Transactions on Smart Processing and Computing
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• v.6 no.3
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• pp.193-199
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• 2017

Instead of using only spatial features from a single frame for person re-identification, a combination of spatial and temporal factors boosts the performance of the system. A recurrent neural network (RNN) shows its effectiveness in generating highly discriminative sequence-level human representations. In this work, we implement RNN, three Long Short Term Memory (LSTM) network variants, and Gated Recurrent Unit (GRU) on Caffe deep learning framework, and we then conduct experiments to compare performance in terms of size and accuracy for person re-identification. We propose using GRU for the optimized choice as the experimental results show that the GRU achieves the highest accuracy despite having fewer parameters than the others.

• Journal of Multimedia Information System
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• v.2 no.1
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• pp.153-162
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• 2015

In today's pervasive computing environments, multimedia content should be adapted to meet various conditions of network connections, terminals, and user characteristics. Scalable Video Coding (SVC) is a key solution for video communication over heterogeneous networks, where user terminals have different capabilities. This paper presents a standard-compliant approach that adapts an SVC bitstream to support multiple users. The adaptation problem is formulated as an optimization problem, focusing on the tradeoff between qualities of different spatial layers of an SVC video. Then the adaptation process is represented by standard metadata of MPEG-21, which can be solved by universal processing to enable interoperable and automatic operation. Our approach provides the users with optimal quality, a wide flexibility, and seamless adaptation. To the best of our knowledge, this is the first study that shows the adaptation tradeoff between spatial layers of a conforming SVC bitstream.

• Journal of Korean Association for Spatial Structures
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• v.2 no.3 s.5
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• pp.61-70
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• 2002

The objective of this study is the development of a size and shape discrete optimum design algorithms, which is based on the genetic algorithms and the fuzzy theory. This algorithms can perform both size and shape optimum designs of plane and space trusses. The developed fuzzy shape-GAs (FS-GAs) was implemented in a computer program. For the optimum design, the objective function is the weight of structures and the constraints are limits on loads and serviceability. This study solves the problem by introducing the FS-GAs operators into the genetic.