• Proceedings of the Korea Contents Association Conference
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• 2006.11a
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• pp.626-630
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• 2006

In this paper, I proposed the algorithm that realize scheduler of WRR method in mobile network and analyze the performance of the proposed algorithm. The need for providing quality of service(QoS) for real-time applications in wireless networks has been driving research activities and standardization efforts for some time. In particular, there have been considerable research of scheduling algorithm for wireless environments. The BSW algorithm of WRR method that is suited to wireless environment is developed to the results of these effort. But BSW algorithm is deteriorated the performance by realization complexity in wireless environment is necessary to fast scheduling. To solve of these problem this paper proposed the scheduling algorithm which degrades of implementation complexity and which improves the performance and analysis of the performance of the proposed algorithm.

• The KIPS Transactions:PartB
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• v.11B no.7 s.96
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• pp.867-874
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• 2004

K-Means algorithm is a non-hierarchical (plat) and reassignment techniques and iterates algorithm steps on the basis of K cluster centroids until the clustering results converge into K clusters. In its nature, K-Means algorithm has characteristics which make different results depending on the initial and new centroids. In this paper, we propose the modified K-Means algorithm which improves the initial and new centroids decision methodologies. By evaluating the performance of two algorithms using the 16 weighting scheme of SMART system, the modified algorithm showed $20{\%}$ better results on recall and F-measure than those of K-Means algorithm, and the document clustering results are quite improved.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.27 no.5C
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• pp.435-444
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• 2002

In this paper, a novel packet scheduling algorithm, so-called the CSL algorithm is discussed, whereby the firewall property as well as the deterministic delay bound guarantee are supported in session level. Lots of simulation studies validate those properties of the CSL algorithm. The CSL algorithm is distingushable from the well- known EDD scheme in terms of the firewall property. Regarding the implementation complexity, the CSL algorithm turns out to be of 0(1) besides the sorting overhead. Owing to the maintained generic fair queueing structure in the CSL algorithm, a various fair queueing schemes can be applied with minor modification. For the TCP/IP network which is vulnerable to the misbehaving traffic sources, the firewall property of the CSL algorithm is quite useful for the advanced quality of services.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.3
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• pp.976-990
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• 2020

The k-means algorithm is widely used in academia and industry due to easy and simple implementation, enabling fast learning for complex datasets. However, k-means struggles to classify datasets without prior knowledge of specific domains. We proposed the repulsive k-means (RK-means) algorithm in a previous study to improve the k-means algorithm, using the repulsive force concept, which allows deleting unnecessary cluster centroids. Accordingly, the RK-means enables to classifying of a dataset without domain knowledge. However, three main problems remain. The RK-means algorithm includes a cluster repulsive force offset, for clusters confined in other clusters, which can cause cluster locking; we were unable to prove RK-means provided optimal convergence in the previous study; and RK-means shown better performance only normalize term and weight. Therefore, this paper proposes the advanced RK-means (ARK-means) algorithm to resolve the RK-means problems. We establish an initialization strategy for deploying cluster centroids and define a metric for the ARK-means algorithm. Finally, we redefine the mass and normalize terms to close to the general dataset. We show ARK-means feasibility experimentally using blob and iris datasets. Experiment results verify the proposed ARK-means algorithm provides better performance than k-means, k'-means, and RK-means.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.36 no.3C
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• pp.183-189
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• 2011

The LMS(Least Mean Square) algorithm is generally used because of tenacity, high mating spots and simplicity of realization. But the LMS algorithm has trade-off between nonuniform collect and EMSE(Excess Mean Square Error). To overcome this weakness, variable step size is used widely but it needs a lot of calculation load. In this paper we consider new algorithm, which can reduce calculations and adapt in case of environment changes, uses original signal and noise signal of IGC(Instantaneous Gain Control). For the real time processing of IGC algorithm, we remove the logarithmic function. The performance of proposed algorithm is tested to adaptive noise canceller in automobile. We show implemented LabVIEW FPGA system of IGC algorithm is more efficient than others.

• Journal of the Korea Society of Computer and Information
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• v.13 no.2
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• pp.243-250
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• 2008

The coverage algorithm based on Boustrophedon path has been known to be the most efficient in places without or less obstacles If the map of an environmental area thru SLAM algorithm can be obtainable. However, the efficiency of the coverage algorithm based on Boustrophedon path drops drastically when obstacles are complex. In this paper, we propose and implement a new algorithm, which we call Group-k, that efficiently handles the complex area. The Group-k algorithm groups the obstacles and prioritizes the covering sequences with complex rank of the groups. Implementation-based experiments show about 20% improved performance when applying the nor- algorithm, compared to the Boustrophedon path algorithm.

• The Journal of the Korea Contents Association
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• v.21 no.7
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• pp.164-170
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• 2021

In VLSI design, partitioning is a task of clustering objects into groups so that a given objective circuit is optimized. It is used at the layout level to find strongly connected components that can be placed together in order to minimize the layout area and propagation delay. The most popular algorithms for partitioning include the Kernighan-Lin algorithm, Fiduccia-Mattheyses heuristic and simulated annealing. In this paper, we propose a adapted genetic algorithm searching solution space for the circuit partitioning problem, and then compare it with simulated annealing and genetic algorithm by analyzing the results of implementation. As a result, it was found that an adaptive genetic algorithm approaches the optimal solution more effectively than the simulated annealing and genetic algorithm.

• 한국HCI학회:학술대회논문집
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• 2008.02a
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• pp.230-235
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• 2008

This paper addresses issues associated with the real-time implementation of a wideband speech codec such as ITU-T G. 729. 1 on an ARM processor in order to provide an improved voice quality of a VoWiFi service. The real-time implementation features in optimizing the C-source code of G.729. 1 and replacing several parts of the codec algorithm with faster ones. The performance of the implementation is measured by the CPU time spent for G.729.1 on the ARM926EJ processor that is used for a VoWiFi phone. It is shown from the experiments that the G.729.1 codec works in real-time with better voice quality than G 729 codec that is conventionally used for VoIP or VoWiFi phones.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.7
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• pp.3543-3557
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• 2017

Compression is a very important technique for remotely sensed hyperspectral images. The lossless compression based on the recursive least square (RLS), which eliminates hyperspectral images' redundancy using both spatial and spectral correlations, is an extremely powerful tool for this purpose, but the relatively high computational complexity limits its application to time-critical scenarios. In order to improve the computational efficiency of the algorithm, we optimize its serial version and develop a new parallel implementation on graphics processing units (GPUs). Namely, an optimized recursive least square based on optimal number of prediction bands is introduced firstly. Then we use this approach as a case study to illustrate the advantages and potential challenges of applying GPU parallel optimization principles to the considered problem. The proposed parallel method properly exploits the low-level architecture of GPUs and has been carried out using the compute unified device architecture (CUDA). The GPU parallel implementation is compared with the serial implementation on CPU. Experimental results indicate remarkable acceleration factors and real-time performance, while retaining exactly the same bit rate with regard to the serial version of the compressor.

• Proceedings of the Korean Society for Technology of Plasticity Conference
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• 2007.05a
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• pp.272-275
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• 2007

This paper is concerned with modified integration algorithm on the strain-space for rate and temperature dependent elasto-plastic constitutive relations in order to obtain more accurate results in numerical implementation. The proposed algorithm is integrated analytically using integration by part and chain rule and then is applied to the 2-stage Lobatto IIIA with second-order accuracy. It has advantage that is able to consider the convective stress rates on the yield surface of the strain-space. Also this paper is carried out the iteration procedure using the Newton-Raphson method to enforce consistency at the end of the step. And the performance of the proposed algorithm for rate and temperature dependent constitutive relation is illustrated by means of analysis of adiabatic shear bands.