• Journal of Korea Society of Industrial Information Systems
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• v.12 no.1
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• pp.54-60
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• 2007

The Digital Multimedia Broadcasting(DMB) system is developed to offer high quality multimedia content to the mobile environment. The system adopts the MPEG-4 standard for the main video, audio and other media format. For providing interactive contents, it also adopts the MPEG-4 scene description that refers to the spatio-temporal specifications and behaviors of individual objects. With more interactive contents, the scene description also needs higher bitrate. However, the bandwidth for allocating meta data, such as scene description is restrictive in the mobile environment. On one hand, the DMB terminal renders each media stream according to the scene description. Thus the binary format for scene(BIFS) stream corresponding to the scene description should be decoded and parsed in advance when presenting media data. With this reasoning, the transmission delay of the BIFS stream would cause the delay in transmitting whole audio-visual scene presentations, although the audio or video streams are encoded in very low bitrate. This paper presents the effective optimization technique in adapting the BIFS stream into the expected bitrate without any waste in bandwidth and avoiding transmission delays inthe initial scene description for interactive DMB content.

• Management Science and Financial Engineering
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• v.13 no.1
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• pp.35-53
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• 2007

We consider a(worst-case) robust optimization version of the Economic Order Quantity(EOQ) model. Order setup costs and inventory carrying costs are assumed to have uncertainty in their values, and the uncertainty description of the two parameters is supposed to be given by an ellipsoidal representation. A genetic algorithm combined with Monte Carlo simulation is proposed to approximate the ellipsoidal representation. The objective function of the model under ellipsoidal uncertainty description is derived, and the resulting problem is solved by another genetic algorithm. Computational test results are presented to show the performance of the proposed method.

• Steel and Composite Structures
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• v.47 no.5
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• pp.569-585
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• 2023

This paper proposes an efficient approach for the structural topology optimization of bi-directional functionally graded structures by incorporating popular radial basis functions (RBFs) into an implicit level set (ILS) method. Compared to traditional element density-based methods, a level set (LS) description of material boundaries produces a smoother boundary description of the design. The paper develops RBF implicit modeling with multiquadric (MQ) splines, thin-plate spline (TPS), exponential spline (ES), and Gaussians (GS) to define the ILS function with high accuracy and smoothness. The optimization problem is formulated by considering RBF-based nodal densities as design variables and minimizing the compliance objective function. A LS-RBF optimization method is proposed to transform a Hamilton-Jacobi partial differential equation (PDE) into a system of coupled non-linear ordinary differential equations (ODEs) over the entire design domain using a collocation formulation of the method of lines design variables. The paper presents detailed mathematical expressions for BiDFG beams topology optimization with two different material models: continuum functionally graded (CFG) and mechanical functionally graded (MFG). Several numerical examples are presented to verify the method's efficiency, reliability, and success in accuracy, convergence speed, and insensitivity to initial designs in the topology optimization of two-dimensional (2D) structures. Overall, the paper presents a novel and efficient approach to topology optimization that can handle bi-directional functionally graded structures with complex geometries.

• Journal of Broadcast Engineering
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• v.11 no.3 s.32
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• pp.363-378
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• 2006

The Digital Multimedia Broadcasting(DMB) system is developed to offer high quality audio-visual multimedia contents to the mobile environment. The system adopts MPEG-4 standard for the main video, audio and other media format. It also adopts the MPEG-4 scene description for interactive multimedia contents. The animated and interactive contents can be actualized by BIFS(Binary Format for Scene), the binary format for scene description that refers to the spatio-temporal specifications and behaviors of the individual objects. As more interactive contents are, the scene description is also needed more high bitrate. However, the bandwidth for allocating meta data such as scene description is restrictive in mobile environment. On one hand, the DMB terminal starts demultiplexing content and decodes individual media by its own decoder. After decoding each media, rendering module presents each media stream according to the scene description. Thus the BIFS stream corresponding to the scene description should be decoded and parsed in advance of presenting media data. With these reason, the transmission delay of BIFS stream causes the delay of whole audio-visual scene presentation although the audio or video streams are encoded in very low bitrate. This paper presents the effective optimization technique for adapting BIFS stream into expected MPEG-2 TS bitrate without any bandwidth waste and avoiding the transmission delay of the initial scene description for interactive DMB contents.

• ETRI Journal
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• v.32 no.5
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• pp.795-800
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• 2010

Embedding a large vocabulary speech recognition system in mobile devices requires a reduced acoustic model obtained by eliminating redundant model parameters. In conventional optimization methods based on the minimum description length (MDL) criterion, a binary Gaussian tree is built at each state of a hidden Markov model by iteratively finding and merging similar mixture components. An optimal subset of the tree nodes is then selected to generate a downsized acoustic model. To obtain a better binary Gaussian tree by improving the process of finding the most similar Gaussian components, this paper proposes a new distance measure that exploits the difference in likelihood values for cases before and after two components are combined. The mixture weight of Gaussian components is also introduced in the component merging step. Experimental results show that the proposed method outperforms MDL-based optimization using either a Kullback-Leibler (KL) divergence or weighted KL divergence measure. The proposed method could also reduce the acoustic model size by 50% with less than a 1.5% increase in error rate compared to a baseline system.

• The Journal of the Acoustical Society of Korea
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• v.29 no.1
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• pp.56-61
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• 2010

This paper describes optimization methods of acoustic models in HMM-based continuous speech recognition. Most of the conventional speech recognition systems use the same number of Gaussian mixture components for each HMM state. However, since the number of data samples available for each state is different from each other, it is possible to reduce the overall number of model parameters and the computational cost at the decoding step by optimizing the number of Gaussian mixture components. In this study, we introduced the Gaussian mixture weight term at the merging stage of Gaussian components in the minimum description length (MDL) based acoustic modeling optimization. Experimental results showed that the proposed method can obtain better ASR accuracy than the previous optimization method which does not consider the Gaussian mixture weight term.

• Management Science and Financial Engineering
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• v.13 no.1
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• pp.1-24
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• 2007

I propose new combined randomized methods for global optimization problems. These methods are based on the Nested Partitions(NP) method, a useful method for simulation optimization which guarantees global optimal solution but has several shortcomings. To overcome these shortcomings I hired various statistical selection methods and combined with NP method. I first explain the NP method and statistical selection method. And after that I present a detail description of proposed new combined methods and show the results of an application. As well as, I show how these combined methods can be considered in case of computing budget limit problem.

• Journal of Broadcast Engineering
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• v.9 no.1
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• pp.17-31
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• 2004

This paper proposes an algorithm for the robust transmission of video in error Prone environment using multiple description codingby optimal split of DCT coefficients and rate-distortionoptimization framework. In MDC, a source signal is split Into several coded streams, which is called descriptions, and each description is transmitted to the decoder through different channel. Between descriptions, structured correlations are introduced at the encoder, and the decoder exploits this correlation to reconstruct the original signal even if some descriptions are missing. It has been shown that the MDC is more resilient than the singe description coding(SDC) against severe packet loss ratecondition. But the excessive redundancy in MDC, i.e., the correlation between the descriptions, degrades the RD performance under low PLR condition. To overcome this Problem of MDC, we propose a hybrid MDC method that controls the SDC/MDC switching according to channel condition. For example, the SDC is used for coding efficiency at low PLR condition and the MDC is used for the error resilience at high PLR condition. To control the SDC/MDC switching in the optimal way, RD optimization framework are used. Lagrange optimization technique minimizes the RD-based cost function, D+M, where R is the actually coded bit rate and D is the estimated distortion. The recursive optimal pet-pixel estimatetechnique is adopted to estimate accurate the decoder distortion. Experimental results show that the proposed optimal split of DCT coefficients and SD/MD switching algorithm is more effective than the conventional MU algorithms in low PLR conditions as well as In high PLR condition.

• The KIPS Transactions:PartA
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• v.14A no.1 s.105
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• pp.31-38
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• 2007

Code Optimization is converting to a code that is equivalent to given program but more efficient, and this process is processed in Code Optimizer. This paper designed and processed Code Optimizer Generator that automatically generates Code Optimizer. In other words Code Optimizer is automatically generated for DFA Pattern Matching which finds the optimal code for the incoming pattern description. DFA Pattern Matching removes redundancy comparisons that occur when patterns are sought for through normalization process and improves simplification and structure of pattern shapes for low cost. Automatic generation of Code Optimization for DFA Pattern Matching eliminates extra effort to generate Code Optimizer every time the code undergoes various transformations, and enables formalism of Code Optimization. Also, the advantage of making DFA for optimization is that it is faster and saves cost of Code Optimizer Generator.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.65 no.12
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• pp.2069-2074
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• 2016

This paper presents a methodology based on evolutionary optimization for simultaneously optimizing design parameters of controller and components of plant. Genetic programming(GP) based bond graph model generation is adopted to open-ended search for the plant. Also GP is applied to represent the controller with a unified method. The formulations of simultaneous plant-controller design optimization problem and the description of solution techniques based on bond graph are derived. A feasible solutions for a plant/controller design using the simultaneous optimization methodology is illustrated.