• Proceedings of the Korean Operations and Management Science Society Conference
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• 2005.05a
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• pp.579-584
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• 2005

A metric is a measure of one factor of a company's performance. The metrics are used to monitor the overall performance of the company for achieving business objectives. Insufficient metrics cannot reflect company's conditions. Therefore, it is important to be equipped with 'good' metrics. This study introduces the concept of metric quality and proposes its dimensions. The study also presents application scenarios that show the role and usefulness of the metric quality.

• Journal of Korean Society for Quality Management
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• v.27 no.4
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• pp.229-240
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• 1999

Drawbacks of using sigma level as a performance metric is reviewed. The concept of sigma level is introduced and methods of calculating sigma levels for various cases are illustrated with examples. Drawbacks of using sigma level as performance metric are also discussed with some suggestions for overcoming them.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.52 no.7
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• pp.434-441
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• 2003

This paper proposes a new quantitative and objective image quality metric which is essential to verify the performance of block-based DCT image coding. The proposed metric considers not only global distortion of coded image such as spatial frequency sensitivity and channel masking using HVS based multi-channel model, but also structural distortions caused block-based coding. The experimental results show a strong correlation between proposed metric and subjective metric.

• The Transactions of the Korean Institute of Electrical Engineers C
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• v.52 no.7
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• pp.434-434
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• 2003

This paper proposes a new quantitative and objective image quality metric which is essential to verify the performance of block-based DCT image coding The proposed metric considers not only global distortion of coded image such as spatial frequency sensitivity and channel masking using HVS based multi-channel model, but also structural distortions caused block-based coding. The experimental results show a strong correlation between propose(B metric and subjective metric.

• Journal of Korea Multimedia Society
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• v.14 no.6
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• pp.711-718
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• 2011

The k-Nearest Neighbor classifier that does not require a training phase is appropriate for a variable number of classes problem like face recognition, Recently distance metric learning methods that is trained with a given data set have reported the significant improvement of the kNN classifier. However, the performance of a distance metric learning method is variable for each application, In this paper, we focus on the face recognition and compare the performance of the state-of-the-art distance metric learning methods, Our experimental results on the public face databases demonstrate that the Mahalanobis distance metric based on PCA is still competitive with respect to both performance and time complexity in face recognition.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.24 no.10A
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• pp.1563-1570
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• 1999

This paper relates to the soft decision method with erasure technique in digital terrestrial television broadcasting system. The proposed decoder use the CSI derived from using the pilots in receiver. The active real(I) and imaginary(Q) data are transferred to the branch metric calculation block that decides the Euclidean distance for the soft decision decoding and also the estimated CSI values are transferred to the same block. After calculating the Euclidean distance for the soft decision decoding, the Euclidean distance of branch metric is multiplied by CSI. To do so, new branch metric values that consider each carrier state information are obtained. We simulated this method in better performance of about 0.15dB to 0.17dB and 2.2dB to 2.9dB in Rayleigh channel than that of the conventional soft decision Viterbi decoding with or without bit interleaver where the constellation is QPSK, 16-QAM and 64-QAM.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.11 no.5
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• pp.731-737
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• 2000

In this paper we propose a decoding algorithm of Ungerboeck TCM/PSK in the concept of Radix-trellis, which has been applied to the decoding of convolutional codes for the high speed decoding. As an example we choose 16-state trellis coded 8-ary PSK. For Radix-4 and Radix-16 trellis decoding, we explain the path metric(PM) and the branch metric(BM) calculation. By using the simulation, we evaluate the bit error rate(BER) performance according to the number of binary digits for I-Q value, PM and BM registers. The proper number of binary digits of each register has been derived.

• Journal of Information Processing Systems
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• v.15 no.5
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• pp.1108-1118
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• 2019

Non-local means (NLM) algorithm is an effective and successful denoising method, but it is computationally heavy. To deal with this obstacle, we propose a novel NLM algorithm with fuzzy metric (FM-NLM) for image denoising in this paper. A new feature metric of visual features with fuzzy metric is utilized to measure the similarity between image pixels in the presence of Gaussian noise. Similarity measures of luminance and structure information are calculated using a fuzzy metric. A smooth kernel is constructed with the proposed fuzzy metric instead of the Gaussian weighted L2 norm kernel. The fuzzy metric and smooth kernel computationally simplify the NLM algorithm and avoid the filter parameters. Meanwhile, the proposed FM-NLM using visual structure preferably preserves the original undistorted image structures. The performance of the improved method is visually and quantitatively comparable with or better than that of the current state-of-the-art NLM-based denoising algorithms.

• Journal of the Korea Safety Management & Science
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• v.15 no.1
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• pp.293-301
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• 2013

The purpose of this study is to introduce the limit of previously used six sigma quality process evaluation metrics, $Z_{st}$ and $P_{pk}$, and a solution to overcome this drawback by using a metric based on performance evaluation of Z-factor quality innovation. Case analysis on projects from national six sigma contest from 2011 to 2012 is performed and literature review on new drug development HTS (High Throughput Screening) is used to propose innovative performance evaluation metrics. This research shows that experimental study on six sigma evaluation metric, $Z_{st}$ and $P_{pk}$, have no significance difference between industrial type (Manufacturing, Semi-Public Institute, Public Institute) and CTQ type (Product Technology Type CTQ, Process Technology Type CTQ). Following discovery characterize this quality improvement as fixed target type project. As newly developed moving target type of quality innovation performance metric Z-Factor is used for evaluating experimental study, hypothetical analysis suggests that $Z_{st}$ and $P_{pk}$ share different relationship or even show reciprocal relationship. Constraints of the study are relatively small sample size of only 37 projects from past 2 years and conflict on having interview and communication with six sigma quality practitioner for qualitative experimental study. Both moving target type six sigma innovation project and fixed target type improvement project or quality circle enables efficient ways for a better understanding and quality practitioner use by applying quality innovation performance metric. Downside of fixed target type quality performance evaluation metric, $Z_{st}$ and $P_{pk}$, is presented through experimental study. In contrast, advantage of this study is that high throughput requiring product technology, process technology and quantum leap typed innovation effect is evaluated based on precision and accuracy and Z-Factor that enables relative comparison between enterprises is proposed and implemented.

• Journal of Broadcast Engineering
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• v.21 no.2
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• pp.157-168
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• 2016

In image processing and computer vision fields, mean squared error (MSE) has popularly been used as an objective metric in image quality optimization problems due to its desirable mathematical properties such as metricability, differentiability and convexity. However, as known that MSE is not highly correlated with perceived visual quality, much effort has been made to develop new image quality assessment (IQA) metrics having both the desirable mathematical properties aforementioned and high prediction performances for subjective visual quality scores. Although recent IQA metrics having the desirable mathematical properties have shown to give some promising results in prediction performance for visual quality scores, they also have high computation complexities. In order to alleviate this problem, we propose a new fast IQA metric using a simple Laplace operator. Since the Laplace operator used in our IQA metric can not only effectively mimic operations of receptive fields in retina for luminance stimulus but also be simply computed, our IQA metric can yield both very fast processing speed and high prediction performance. In order to verify the effectiveness of the proposed IQA metric, our method is compared to some state-of-the-art IQA metrics. The experimental results showed that the proposed IQA metric has the fastest running speed compared the IQA methods except MSE under comparison. Moreover, our IQA metric achieves the best prediction performance for subjective image quality scores among the state-of-the-art IQA metrics under test.