• Journal of Environmental Policy
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• v.9 no.2
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• pp.41-55
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• 2010

This paper analyzes optimal watershed management focusing on reservoir-level sediment removal techniques. Although dams and reservoirs provide several benefits, sedimentation may reduce their storage capacity. As of today, the Aswan High Dam (AHD) in Egypt faces approximately 76% reduced life of the reservoir. Since the AHD is the major fresh water source in Egypt, sustainable use of this resource is extremely important. A model is developed to simultaneously determine optimal sediment removal strategies for upstream soil conservation efforts and reservoir-level sediment control. Two sediment removal techniques are considered: mechanical dredging and hydro-suction sediment removal system (HSRS). Moreover, different levels of upstream soil conservation efforts have introduced to control soil erosion, which is a major contributor of reservoir storage capacity reduction. We compare a baseline case, which implies no management alternative, to non-cooperative and social planners' solution. Our empirical results indicate that the socially optimal sediment removal technique is a mechanical dredging with unconstrained amount with providing a sustainable life of the reservoir. From the empirical results, we find that social welfare can be as high as $151.01 billion, and is sensitive to interest rates and agricultural soil loss.

• The Journal of the Acoustical Society of Korea
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• v.22 no.8
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• pp.637-644
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• 2003

In this study, with the FEM we analyzed the variation of the resonance frequency, bandwidth, and sound pressure of the Tonpilz transducer in relation to its design variables. Through statistical multiple regression analysis of the results, we derived functional forms of the resonance frequency, bandwidth, and sound pressure in terms of the design variables. By applying the constrained optimization technique, SQP-PD, to the derived function, we determined the optimal structure of the transducer that could provide the highest sound pressure level at the resonance frequency of 30,000 Hz and having the -3 dB bandwidth more than 10%, The validity of the optimized results was confirmed through comparison of the optimal performance with that of the FEA. The optimal design method proposed could reflect all the cross-coupled effects of multiple structural variables, and could determine the detailed geometry of the transducer with great efficiency and rapidity.

• Journal of the Korean Society of Hazard Mitigation
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• v.10 no.4
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• pp.9-16
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• 2010

In the health monitoring of civil engineering structures, the optimal sensor placement has a major influence on the quality of the results. This paper considers the problem of locating sensors with the aim of maximizing the data information so that structural parameters or damage of structures can be assessed. An proposed technique using a genetic algorithm is introduced to find the optimal placement of sensors. The sensitivity on modal vectors by structural parameters and the orthogonality of modal vectors have been taken as the fitness function of the genetic algorithm. A simple tower structure is used for example analyses to investigate the feasibility and applicability of the proposed approach. The example analyses show the way how the modal sensitivity and the modal orthogonality in the fitness function have influence on the optimal sensor placement. It is shown that the present method using the proposed fitness function can provide the reliable results.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.28 no.8A
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• pp.581-590
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• 2003

This paper proposes the routing path selection mechanism for source routing-based PtMP (Point-to-Multipoint) call in ATM switching system. Especially, it suggests PtMP routing path selection method that can share the maximum resource prior to the optimal path selection, guarantee the reduction of path calculation time and cycle prevention. The searching for the nearest branch point from destination node to make the maximum share of resource is the purpose of this algorithm. Therefore among neighbor nodes from destination node by back-tracking, this algorithm fixes the node crossing first the node on existing path having the same Call ID as branch node, constructs the optimal PtMP routing path. The optimal node to be selected by back-tracking is selected by the use of Dijkstra algorithm. That is to say, PtMP routing path selection performs the step of cross node selection among neighboring nodes by back-tracking and the step of optimal node selection(optimal path calculation) among neighboring nodes by back-tracking. This technique reduces the process of search of routing information table for path selection and path calculation, also solves the cycle prevention easily during path establishment.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.11
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• pp.1545-1550
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• 2021

We propose an optimal variable step size adjustment method for the simplified subband affine projection algorithm (Simplified SAP; SSAP) in a subband structure based on a polyphase decomposition technique. The proposed method provides an optimal step size derived to minimize the mean square deviation(MSD) at the time of updating the coefficients of the subband adaptive filter. Application of the proposed optimal step size in the SSAP algorithm using colored input signals ensures fast convergence speed and small steady-state error. The results of computer simulations performed using AR(2) signals and real voices as input signals prove the validity of the proposed optimal step size for the SSAP algorithm. Also, the simulation results show that the proposed algorithm has a faster convergence rate and good steady-state error compared to the existing other adaptive algorithms.

• Journal of the Korean Society of Food Culture
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• v.37 no.4
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• pp.335-344
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• 2022

The study was aimed to investigate the operational meal costs by kindergarten size in Seoul and to analyze recognition for optimal meal prices. A survey (31.6% recovery rate) was conducted on all kindergartens (779 kindergartens) in Seoul on April 2021 using descriptive analysis, t-test, and dispersion method. A price sensitivity measurement (psm) method was used to determine optimal meal prices. Result showed an average food cost for kindergartens of 2,647 won, an average labor cost of 605 won, an average operating cost of 146 won, and the total meal cost of 3,506 won. Total meal cost decreased with increasing kindergarten size (p<0.001). On the other hand, kindergartens with more students decreased the ratio of food cost to total meal cost, and operating cost and labor costs (p<0.001) increased. The optimal price of kindergarten operators' meal cost (OPP) was KRW 3,673. Furthermore, the analysis showed the sensitivity of operators' meal costs to kindergarten size was insignificant.

• Convergence Security Journal
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• v.23 no.5
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• pp.3-8
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• 2023

The Fourth Industrial Revolution is bringing about great changes in many industrial fields, and among them, active research is being conducted on convergence technology using artificial intelligence. Among them, the demand is increasing day by day in the field of object recognition using artificial intelligence and digital transformation using recognition results. In this paper, we proposed an optimal learning model construction method to accurately recognize letters, symbols, and lines in images and save the recognition results as files in a standardized format so that they can be used in simulations. In order to recognize letters, symbols, and lines in images, the characteristics of each recognition target were analyzed and the optimal recognition technique was selected. Next, a method to build an optimal learning model was proposed to improve the recognition rate for each recognition target. The recognition results were confirmed by setting different order and weights for character, symbol, and line recognition, and a plan for recognition post-processing was also prepared. The final recognition results were saved in a standardized format that can be used for various processing such as simulation. The excellent performance of building the optimal learning model proposed in this paper was confirmed through experiments.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.31 no.6_2
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• pp.577-583
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• 2013

Recently, massive archives of ground information imagery from new sensors have become available. To establish a functional relationship between the image and the ground space, sensor models are required. The rational functional model (RFM), which is used as an alternative to the rigorous sensor model, is an attractive option owing to its generality and simplicity. To determine the rational polynomial coefficients (RPC) in RFM, however, we encounter the problem of obtaining a stable solution. The design matrix for solutions is usually ill-conditioned in the experiments. To solve this unstable solution problem, regularization techniques are generally used. In this paper, we describe the effective determination of the optimal regularization parameter in the regularization technique during RPC derivation. A brief mathematical background of RFM is presented, followed by numerical approaches for effective determination of the optimal regularization parameter using the Euler Method. Experiments are performed assuming that a tilted aerial image is taken with a known rigorous sensor. To show the effectiveness, calculation time and RMSE between L-curve method and proposed method is compared.

• Journal of Korea Multimedia Society
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• v.20 no.8
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• pp.1406-1420
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• 2017

Artificial neural networks (ANNs) play an important role in the fields of function approximation, prediction, and classification. ANN performance is critically dependent on the input parameters, including the number of neurons in each layer, and the optimal values of weights and biases assigned to each neuron. In this study, we apply the particle swarm optimization method, a popular optimization algorithm for determining the optimal values of weights and biases for every neuron in different layers of the ANN. Several regression models, including general linear regression, Fourier regression, smoothing spline, and polynomial regression, are conducted to evaluate the proposed method's prediction power compared to multiple linear regression (MLR) methods. In addition, residual analysis is conducted to evaluate the optimized ANN accuracy for both training and test datasets. The experimental results demonstrate that the proposed method can effectively determine optimal values for neuron weights and biases, and high accuracy results are obtained for prediction applications. Evaluations of the proposed method reveal that it can be used for prediction and estimation purposes, with a high accuracy ratio, and the designed model provides a reliable technique for optimization. The simulation results show that the optimized ANN exhibits superior performance to MLR for prediction purposes.

• Advances in Energy Research
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• v.5 no.1
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• pp.31-55
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• 2017

In the present study, PV/T collector was modeled via analysis of governing equations and physics of the problem. Specifications of solar radiation were computed based on geographical characteristics of the location and the corresponding time. Temperature of the collector plate was calculated as a function of time using the energy equations and temperature behavior of the photovoltaic cell was incorporated in the model with the aid of curve fitting. Subsequently, operational range for reaching to maximal efficiency was studied using Genetic Algorithm (GA) technique. Optimization was performed by defining an objective function based on equivalent value of electrical and thermal energies. Optimal values for equipment components were determined. The optimal value of water flow rate was approximately 1 gallon per minute (gpm). The collector angle was around 50 degrees, respectively. By selecting the optimal values of parameters, efficiency of photovoltaic collector was improved about 17% at initial moments of collector operation. Efficiency increase was around 5% at steady condition. It was demonstrated that utilization of photovoltaic collector can improve efficiency of solar energy-based systems.