• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.7
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• pp.2957-2980
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• 2020

Ensemble clustering commonly integrates multiple basic partitions to obtain a more accurate clustering result than a single partition. Specifically, it exists an inevitable problem that the incomplete transformation from the original space to the integrated space. In this paper, a novel ensemble clustering algorithm using a newly reconstructed mapping coefficient (ECRMC) is proposed. In the algorithm, a newly reconstructed mapping coefficient between objects and micro-clusters is designed based on the principle of increasing information entropy to enhance effective information. This can reduce the information loss in the transformation from micro-clusters to the original space. Then the correlation of the micro-clusters is creatively calculated by the Spearman coefficient. Therefore, the revised co-association graph between objects can be built more accurately because the supplementary information can well ensure the completeness of the whole conversion process. Experiment results demonstrate that the ECRMC clustering algorithm has high performance, effectiveness, and feasibility.

• Proceedings of the KOSOMBE Conference
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• v.1995 no.11
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• pp.193-196
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• 1995

An algorithm using topological mapping has been developed for a real-time detection of the QRS complexes of ECG signals. As a measurement of QRS complex energy, we used topological mapping from one dimensional sampled ECG signals to two dimensional vectors. These vectors are reconstructed with the sampled ECG signals and the delayed ones. In this method, the detection rates of CRS complex vary with the parameters such as R-R interval average and peak detection threshold coefficient. We use mean, median, and iterative method to determint R-R interval average and peak estimation. We experiment on various value of search back coefficient and peak detection threshold coefficient to find optimal rule.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.33B no.11
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• pp.62-71
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• 1996

In this paper we propose a method that improves PSNR at low bit rate and reduces computational complexity in fractal image coding based on discrete wavelet transform. The proposed method, which uses significant coefficient tree, improves PSNR of the reconstructed image and reduces computational comlexity of mapping domain block onto range block by matching only the significant coefficients of range block to coefficients of domain block. Also, the proposed method reduces error propagation form lower resolution subbands to higher resolution subbands by correcting error of lower resolution subbands. Some experimental results confirm that the proposed method reduces encoding and decoding time significantly and has fine reconstructed images having no blocking effect and clear edges at low bit rate.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.37 no.2A
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• pp.128-134
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• 2012

In this paper, we propose a novel approach to enhance the recognition performance of a far and partially occluded three-dimensional (3-D) target in computational curving-effective integral imaging (CEII) by using the direct pixel-mapping (DPM) method. With this scheme, the elemental image array (EIA) originally picked up from a far and partially occluded 3-D target can be converted into a new EIA just like the one virtually picked up from a target located close to the lenslet array. Due to this characteristic of DPM, resolution and quality of the reconstructed target image can be highly enhanced, which results in a significant improvement of recognition performance of a far 3-D object. Experimental results reveal that image quality of the reconstructed target image and object recognition performance of the proposed system have been improved by 1.75 dB and 4.56% on the average in PSNR (peak-to-peak signal-to-noise ratio) and NCC (normalized correlation coefficient), respectively, compared to the conventional system.