• Journal of the Korea Institute of Information and Communication Engineering
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• v.13 no.10
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• pp.2071-2078
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• 2009

The first frame is encoded in intra mode which generates a larger number of bits. In addition, the first frame is used for the inter mode encoding of the following frames. Thus the intial QP (Quantization Parameter) for the first frame affects the first frame as well as the following frames. Traditionally, the initial QP is determined among four constant values only depending on the bpp. In the case of low bit rate video coding, the initial QP value is fixed to 35 regardless of the output bandwidth. Although this initialization scheme is simple, yet it is not accurate enough. An accurate intial QP prediction scheme should not only depends on bpp but also on the complexity of the video sequence and the output bandwidth. In the proposed scheme, we use a linear model because there is a linear inverse proportional relationship between the output bandwidth and the optimal intial QP. Model parameters of the model are determined depending on the spatial complexity of the first frame. It is shown by experimental results that the new algorithm can predict the optimal initial QP more accurately and generate the PSNR performance better than that of the existing JM algorithm.

• Journal of IKEEE
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• v.3 no.2 s.5
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• pp.305-313
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• 1999

To demodulate the received OFDM signal, symbol timing detection which finds symbol start in the received sample stream is required in the system initialization. In this paper, we analyze the effect of symbol timing offset and propose a new symbol timing detection algorithm, which is using the guard interval. The proposed algorithm requires low computational process and small memory size, and dose not be affected by frequency offset and phase offset. In addition, We apply this algorithm to European digital TV broadcasting model based on OFDM to evaluate the performance in AWGN and multipath fading channel by the computer simulation.

• Journal of Information Processing Systems
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• v.12 no.4
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• pp.555-576
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• 2016

In the conventional clustering algorithms, an object could be assigned to only one group. However, this is sometimes not the case in reality, there are cases where the data do not belong to one group. As against, the fuzzy clustering takes into consideration the degree of fuzzy membership of each pixel relative to different classes. In order to overcome some shortcoming with traditional clustering methods, such as slow convergence and their sensitivity to initialization values, we have used the Harmony Search algorithm. It is based on the population metaheuristic algorithm, imitating the musical improvisation process. The major thrust of this algorithm lies in its ability to integrate the key components of population-based methods and local search-based methods in a simple optimization model. We propose in this paper a new unsupervised clustering method called the Fuzzy Harmony Search-Fourier Transform (FHS-FT). It is based on hybridization fuzzy clustering and the harmony search algorithm to increase its exploitation process and to further improve the generated solution, while the Fourier transform to increase the size of the image's data. The results show that the proposed method is able to provide viable solutions as compared to previous work.

• Bulletin of the Korean Chemical Society
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• v.27 no.2
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• pp.224-230
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• 2006

Escherichia coli transcription termination factor Rho catalyzes the unwinding of RNA/DNA duplex in reactions that are coupled to ATP binding and hydrolysis. We report here the kinetic mechanism of presteady state ATP binding and hydrolysis by the Rho-RNA complex. Presteady state chemical quenched-flow technique under multiple turnover condition was used to probe the kinetics of ATP binding and hydrolysis by the Rho-RNA complex. The quenched-flow presteady state kinetics of ATP hydrolysis studies show that three ATPs are bound to the Rho-RNA complex with a rate of $4.4\;{\times}\;10^5M^{-1}s^{-1}$, which are subsequently hydrolyzed at a rate of $88s^{-1}$ and released during the initiation process. Global fit of the presteady state ATP hydrolysis kinetic data suggests that a rapid-equilibrium binding of ATP to Rho-RNA complex occurs prior to the first turnover and the chemistry step is not reversible. The initial burst of three ATPs hydrolysis was proposed to be involved in the initialization step that accompanies proper complex formation of Rho-RNA. Based on these results a kinetic model for initiation process for Rho-RNA complex was proposed relating the mechanism of ATP binding and hydrolysis by Rho to the structural transitions of Rho-RNA complex to reach the steady state phase, which is implicated during translocation along the RNA.

• Journal of the Korean Institute of Telematics and Electronics
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• v.26 no.3
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• pp.22-31
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• 1989

In this paper, we analyze the performance of the IEEE 802.4 token passing bus protocol through a simulation model of the protocol. In order to analyze performance of the protocol in the initialization, transition and fault recovery states as well as in the steady state, the protocol functions are divided into five processes each of which can effectively simulate protocol behaviors according to the variations of protocol parameters. From the simulation study, we obtain protocol parameters which severely influence the protocol performance and find out that proper selection of the protocol parameter values for token passing is very important to obtain good performance of the protocol when the priority scheme is used.

• The Journal of Information Systems
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• v.27 no.4
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• pp.115-128
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• 2018

Purpose The purpose of this study is to predict future behaviors of business process. Specifically, this study tried to predict the last activities of process instances. It contributes to overcoming the limitations of existing approaches that they do not accurately reflect the actual behavior of business process and it requires a lot of effort and time every time they are applied to specific processes. Design/methodology/approach This study proposed a novel approach based using deep learning in the form of dynamic recurrent neural networks. To improve the accuracy of our prediction model based on the approach, we tried to adopt the latest techniques including new initialization functions(Xavier and He initializations). The proposed approach has been verified using real-life data of a domestic small and medium-sized business. Findings According to the experiment result, our approach achieves better prediction accuracy than the latest approach based on the static recurrent neural networks. It is also proved that much less effort and time are required to predict the behavior of business processes.

• ETRI Journal
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• v.43 no.1
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• pp.120-132
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• 2021

A frequency diverse array (FDA) multiple-input multiple-output (MIMO) radar employs a small frequency increment across transmit elements to produce an angle-range-dependent beampattern for target angle and range detection. The joint angle and range estimation problem is a trilinear model. The traditional trilinear alternating least square (TALS) algorithm involves high computational load due to excessive iterations. We propose a fast-convergence trilinear decomposition (FC-TD) algorithm to jointly estimate FDA-MIMO radar target angle and range. We first use a propagator method to obtain coarse angle and range estimates in the data domain. Next, the coarse estimates are used as initialized parameters instead of the traditional TALS algorithm random initialization to reduce iterations and accelerate convergence. Finally, fine angle and range estimates are derived and automatically paired. Compared to the traditional TALS algorithm, the proposed FC-TD algorithm has lower computational complexity with no estimation performance degradation. Moreover, Cramer-Rao bounds are presented and simulation results are provided to validate the proposed FC-TD algorithm effectiveness.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.2
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• pp.335-352
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• 2023

When solving multi-objective optimization problems, the blindness of the evolution direction of the population gradually emerges with the increase in the number of objectives, and there are also problems of convergence and diversity that are difficult to balance. The many- objective optimization problem makes some classic multi-objective optimization algorithms face challenges due to the huge objective space. The sine cosine algorithm is a new type of natural simulation optimization algorithm, which uses the sine and cosine mathematical model to solve the optimization problem. In this paper, a knee-driven many-objective sine-cosine algorithm (MaSCA-KD) is proposed. First, the Latin hypercube population initialization strategy is used to generate the initial population, in order to ensure that the population is evenly distributed in the decision space. Secondly, special points in the population, such as nadir point and knee points, are adopted to increase selection pressure and guide population evolution. In the process of environmental selection, the diversity of the population is promoted through diversity criteria. Through the above strategies, the balance of population convergence and diversity is achieved. Experimental research on the WFG series of benchmark problems shows that the MaSCA-KD algorithm has a certain degree of competitiveness compared with the existing algorithms. The algorithm has good performance and can be used as an alternative tool for many-objective optimization problems.

• Journal of KIISE:Computer Systems and Theory
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• v.29 no.11
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• pp.589-600
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• 2002

Deformable models offer an attractive approach for extracting three-dimensional boundary structures from volumetric images. However, conventional deformable models have three major limitations - sensitive to initial condition, difficult to represent complex boundaries with severe object concavities and protrusions, and self-intersective between model elements. This paper proposes a deformable model that is effective to extract geometrically complex boundary surfaces by improving away the limitations of conventional deformable models. First, the proposed deformable model resamples its elements hierarchically based on volume image pyramid. The hierarchical resampling overcomes sensitivity to initialization by extracting the boundaries of objects in a multiscale scheme and enhances geometric flexibility to be well adapted to complex image features by refining and regularizing the size of model elements based on voxel size. Second, the physics-based formulation of our model integrates conventional internal and external forces, as well as a non-self-intersecting force. The non-self-intersecting force effectively prevents collision or crossing over between non-neighboring model elements by pushing each other apart if they are closer than a limited distance. We show that the proposed model successively extracts the complex boundaries including severe concavities and protrusions, neither depending on initial position nor causing self-intersection, through the experiments on several computer-generated volume images and brain MR volume images.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.16 no.9
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• pp.1947-1954
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• 2012

The first frame is encoded in intra mode which generates a larger number of bits. In addition, the first frame is used for the inter mode encoding of the following frames. Thus the initial QP for the first frame affects the first frame as well as the following frames. Traditionally, the initial QP is determined among four constant values only depending on the bpp. In the case of low bit rate video coding, the initial QP value is fixed to 40 regardless of the output bandwidth. Although this initialization scheme is simple, yet it is not accurate enough. An accurate initial QP prediction scheme should not only depends on bpp but also on the complexity of the video sequence and the output bandwidth. In the proposed scheme, we determine the initial QP according to the ratio of the first frame to the total bits allocated to a GOP. To estimate the QP of the allocated bits, Rate-QP model is used. It is shown by experimental results that the new algorithm can predict the optimal initial QP more accurately and generate the PSNR performance better than that of the existing JVT algorithm.