• Journal of the Institute of Convergence Signal Processing
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• v.10 no.1
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• pp.32-39
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• 2009

In this paper, the method of region segmentation using genetic algorithm is proposed for an improvement of efficiency in moving picture coding. A genetic algorithm is the method that searches a large probing space using only a function value for a optimal combination consecutively. By progressing both motion presumption and region segmentation at once, we can assign the motion vector in a image to a small block or a pixel respectively, and transform the capacity of coding and a signal to noise rate into a problem of optimization. That is to say, there is close correlation between region segmentation and motion presumption in motion-compensated prediction coding. This is to optimize the capacity of coding and a S/N ratio. This is to arrange the motion vector in each block of picture according to the state of optimization. Therefore, we examined both the data type of genetic algorithm and the method of data processing to obtain the results of optimal region segmentation in this paper. And we confirmed the validity of a proposed method using the test pictures by means of computer simulation.

• Resources Recycling
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• v.31 no.1
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• pp.56-64
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• 2022

Construction waste is generated at a rate of approximately 221,102 tons/day in Korea. In particular, mixed construction waste generates approximately 24,582 tons/day. The other components were recycled by 98.9%. The amount of greenhouse gas emissions from the waste was 17.1 million tons of CO2 equaling 2.3% of the total greenhouse gas emissions. To reduce greenhouse gas emissions, reducing the environmental impact is becoming increasingly important. However, appropriate treatment must first be established, as mixed construction waste is also increasing. Thus, an effective plan is urgently needed because it is frequently segregated and sorted by the landfill and incinerated. In addition, there is an urgent need to prepare various effective recycling methods rather than a simple treatment. Therefore, this study analyzed the environmental impact of the treatment of mixed construction waste by calculating greenhouse gas emissions. As a result, the highest greenhouse gas generation occurred during the incineration stage. Moreover, the optimal method to reduce greenhouse gas emissions is recycling and energy recovery from waste. In addition, the amount of greenhouse gas generated during energy recovery from the waste stage was the second highest. However, greenhouse gas emissions can be reduced by using waste as energy to reduce fossil fuel consumption. In addition, for the transportation stage, the optimal reduction plan is to minimize the amount of greenhouse gas emissions by setting the optimal distance and applying biofuel and electric vehicle operations.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.38A no.7
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• pp.560-570
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• 2013

In this paper, we propose transceiver design strategies for the two-cell multiple-input multiple-output (MIMO) interfering broadcast channel where inter-cell interference (ICI) exists in addition to inter-user interference (IUI). We first formulate the generalized zero-forcing interference alignment (ZF-IA) method based on the alignment of IUI and ICI in multi-dimensional subspace. We then devise a minimum weighted-mean-square-error (WMSE) method based on "regularizing" the precoders and decoders of the generalized ZF-IA scheme. In contrast to the existing weighted-sum-rate-maximizing transceiver, our method does not require an iterative calculation of the optimal weights. Because of this, the proposed scheme, while not designed specially to maximize the sum-rate, is computationally efficient and achieves a faster convergence compared to the known weighed-sum-rate maximizing scheme. Through analysis and simulation, we show the effectiveness of the proposed regularized ZF-IA scheme.

• Journal of KSNVE
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• v.8 no.2
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• pp.267-273
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• 1998

This study aims at performing sensitivity analysis of piezoelectric smart structure for minimizing radiated noise from the structure, The structure consists of a flat plate on which disk shaped piezoelectric actuator is mounted, and finite element modeling is used for the structure. The finite element modeling uses a combination of three dimensional piezoelectric, flat shell and transition elements so thus it can take into account the coupling effects of the piezoelectric device precisely and it can also reduce the degrees of freedom of the finite element model. Electric potential on the piezoelectric actuator is taken as a design variable and total radiated power of the structure is chosen as an objective function. The objective function can be represented as Rayleigh's integral equation and is a function of normal displacements of the structure. For the convenience of computation, all degrees of freedom of the finite element equation is condensed out except the normal displacements of the structure. To perform the design sensitivity analysis, the derivative of the objective function with respect to the normal displacements is found, and the derivative of the norma displacements with respect to the design variable is calculated from the finite element equation by using so called the adjoint variable method. The analysis results are compared with those of the finite difference method, and shows a good agreement. This sensitivity analysis is faster and more accurate than the finite difference method. Once the sensitivity analysis program is used for gradient-based optimizations, one could achieve a better convergence rate than non-derivative methods for optimal design of piezoelectric smart structures.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.24 no.10 s.181
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• pp.2543-2551
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• 2000

Precision injection molding is an important technology for improving productivity and lowering costs in the fields of medical components, lenses and electrical connectors. The quality of injection molded parts is affected by various processing conditions such as filling time and packing pressure profile. It is difficult to consider all the variables at the same time for prediction of the quality. In this study, the genetic algorithm was used to obtain the optimal processing conditions for minimizing the volumetric shrinkage of molded parts. For a higher convergence rate, the method of design of experiments was used to analyze the relationship between processing conditions and volumetric shrinkage of molded parts, which served as analysis tool for the capability of searching optimal processing conditions but also greatly reduces the calculation time by utilizing the information of searching area. As a practical example, compact disks that require micron-level precision were chosen for the study.

• Journal of Communications and Networks
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• v.16 no.5
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• pp.568-577
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• 2014

We consider a mobile content delivery network (mCDN) in which special mobile devices designated as caching servers (caching-server device: CSD) can provide mobile stations with popular contents on demand via device-to-device (D2D) communication links. On the assumption that mobile CSD's are randomly distributed by a Poisson point process (PPP), an optimization problem is formulated to determine the probability of storing the individual content in each server in a manner that minimizes the average caching failure rate. Further, we present a low-complexity search algorithm, optimum dual-solution searching algorithm (ODSA), for solving this optimization problem. We demonstrate that the proposed ODSA takes fewer iterations, on the order of O(log N) searches, for caching N contents in the system to find the optimal solution, as compared to the number of iterations in the conventional subgradient method, with an acceptable accuracy in practice. Furthermore, we identify the important characteristics of the optimal caching policies in the mobile environment that would serve as a useful aid in designing the mCDN.

• Journal of the Korean Institute of Intelligent Systems
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• v.8 no.5
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• pp.29-38
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• 1998

This paper proposes the neural network self-tuning PID controller for the load frequency control of 2- areas power system, namely, the prompt convergence of frequency and tie-line power flow deviation. The neural network applied to computer simulation consists of neurons of two inputs, ten hiddens and tliree outputs layer. Neurons of two inputs layer receive the error and its change rate of the system and cutputs layer consists of three neurons for the parameters of the PID controller. The simulation results shows that the proposed neural network self-tuning PID controller is superior to conventional control t~:chniques(Optimal, PID) in dynamic response and control performance.

• Steel and Composite Structures
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• v.51 no.4
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• pp.417-440
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• 2024

Artificial neural networks (ANN) have been the focus of several studies when it comes to evaluating the pile's bearing capacity. Nonetheless, the principal drawbacks of employing this method are the sluggish rate of convergence and the constraints of ANN in locating global minima. The current work aimed to build four ANN-based prediction models enhanced with methods from the black hole algorithm (BHA), league championship algorithm (LCA), shuffled complex evolution (SCE), and symbiotic organisms search (SOS) to estimate the carrying capacity of piles in cold climates. To provide the crucial dataset required to build the model, fifty-eight concrete pile experiments were conducted. The pile geometrical properties, internal friction angle 𝛗 shaft, internal friction angle 𝛗 tip, pile length, pile area, and vertical effective stress were established as the network inputs, and the BHA, LCA, SCE, and SOS-based ANN models were set up to provide the pile bearing capacity as the output. Following a sensitivity analysis to determine the optimal BHA, LCA, SCE, and SOS parameters and a train and test procedure to determine the optimal network architecture or the number of hidden nodes, the best prediction approach was selected. The outcomes show a good agreement between the measured bearing capabilities and the pile bearing capacities forecasted by SCE-MLP. The testing dataset's respective mean square error and coefficient of determination, which are 0.91846 and 391.1539, indicate that using the SCE-MLP approach as a practical, efficient, and highly reliable technique to forecast the pile's bearing capacity is advantageous.

• Journal of Electrical Engineering and Technology
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• v.10 no.1
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• pp.408-421
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• 2015

Because the wheel of V-belt continuously variable transmission (CVT) system driven by permanent magnet synchronous motor (PMSM) has much unknown nonlinear and time-varying characteristics, the better control performance design for the linear control design is a time consuming job. In order to overcome difficulties for design of the linear controllers, a hybrid recurrent Chebyshev neural network (NN) control system is proposed to control for a PMSM servo-driven V-belt CVT system under the occurrence of the lumped nonlinear load disturbances. The hybrid recurrent Chebyshev NN control system consists of an inspector control, a recurrent Chebyshev NN control with adaptive law and a recouped control. Moreover, the online parameters tuning methodology of adaptive law in the recurrent Chebyshev NN can be derived according to the Lyapunov stability theorem and the gradient descent method. Furthermore, the optimal learning rate of the parameters based on discrete-type Lyapunov function is derived to achieve fast convergence. The recurrent Chebyshev NN with fast convergence has the online learning ability to respond to the system's nonlinear and time-varying behaviors. Finally, to show the effectiveness of the proposed control scheme, comparative studies are demonstrated by experimental results.

• Journal of Institute of Convergence Technology
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• v.4 no.2
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• pp.61-65
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• 2014

Pressure distribution around rotating impeller blades in centrifugal pump has been main issue for design of efficient and high performance automotive water pump. In addition, pressure losses of inlet water pipes should be considered to reduce additional pressure drop and design high performance engine cooling system. In this paper, pressure distribution inside water pump and pressure drop between inlet and outlet of water pump are investigated numerically to design plastic water pump for clean diesel engine application. And the inlet geometry of water pump was considered to analysis the effect of inlet water pipe geometry on pressure distribution around impeller blades and outlet pressure. The prediction results are compared with experimental data to validate and determine optimal operation condition without water pump cavitation. Major design parameters such as blade angle, volute geometry, system pressure, and coolant flow rate are considered to confirm applying possibility of plastic blades to the clean diesel engine.