• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.2
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• pp.495-513
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• 2020

The correlation identification of the subsurface is a novel electrical prospecting method which could suppress stochastic noise. This method is increasingly being utilized by geophysicists. It achieves the frequency response of the underground media through division of the cross spectrum of the input & output signal and the auto spectrum of the input signal. This is subject to the spectral leakage when the cross spectrum and the auto spectrum are computed from cross correlation and autocorrelation function by Discrete Fourier Transformation (DFT, "To obtain an accurate frequency response of the earth system, we propose an improved correlation identification method which uses all phase Fast Fourier Transform (APFFT) to acquire the cross spectrum and the auto spectrum. Simulation and engineering application results show that compared to existing correlation identification algorithm the new approach demonstrates more precise frequency response, especially the phase response of the system under identification.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.36 no.6B
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• pp.600-607
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• 2011

As network traffic is dramatically increasing due to the popularization of Internet, the need for application traffic identification becomes important for the effective use of network resources. In this paper, we present an Internet application traffic identification method based on flow correlation to overcome limitation of signature-based identification methods and to improve performance (completeness) of it. The proposed method can identify unidentified flows from signature-based method using flow correlation between identified and unidentified flows. We propose four separate correlation methods such as Server-Client, Time, Host-Host, and Statistic correlation and describe a flow correlation-based identification system architecture which incorporates the four separate methods. Also we prove the feasibility and applicability of our proposed method by an acceptable experimental result.

• Speech Sciences
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• v.13 no.3
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• pp.155-167
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• 2006

Hearing impairment children possess poor underlying perceptual knowledge of the sound system and show delayed development of segmental organization of that system. The purpose of this study was to investigate the relationship between phonological awareness ability and word identification ability in hearing impaired children. 14 children with moderately severe hearing loss participated in this study. All tasks were individually administered. Phonological awareness tests consisted of syllable blending, syllable segmentation, syllable deletion, body-coda discrimination, phoneme blending, phoneme segmentation and phoneme deletion. Close-set Monosyllabic Words(12 items) and lists 1 and 2 of open-set Monosyllabic Words in EARS-K were examined for word identification. Results of this study were as follows: First, from the phonological awareness task, the close-set word identification showed a high positive correlation with the coda discrimination, phoneme blending and phoneme deletion. The open-set word identification showed a high positive correlation with phoneme blending, phoneme deletion and phoneme segmentation. Second, from the level of phonological awareness, the close-set word identification showed a high positive correlation with the level of body-coda awareness and phoneme awareness while the open-set word identification showed a high positive correlation only with the level of phoneme awareness.

• The Journal of Internal Korean Medicine
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• v.30 no.1
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• pp.200-211
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• 2009

There are many reports about correlations between meteorological elements and stroke. In Oriental medicine, it is recognized that the weather affects the human body and diseases, but there are few studies about the correlation between meteorological elements and pattern identification of stroke. 105 stroke patients classified into fire-heat pattern or dampress-phlegm pattern were registered during the study period. We took the measurement of each meteorological element (atmospheric pressure, temperature, humidity, wind speed) according to pattern identification and analyzed pattern identification into two groups according to mean of each meteorological element during the study period. Mean temperature was higher with the heat-fire pattern than with the dampness-phlegm pattern. Heat-fire pattern also had higher frequency when temperature was higher than mean temperature. There was no correlation between atmospheric pressure, relative humidity, or wind speed and pattern identification.

• Proceedings of the Korea Institute of Convergence Signal Processing
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• 2003.06a
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• pp.134-136
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• 2003

This paper proposes an algorithm for fingerprint identification using phase only correlation. This algorithm uses the phase of fast Fourier transform and correlation function to calculate the similarity. The algorithm gives very clear result for identification because it shows only one conspicuous sharp peak for the same person's fingerprint. Further, it shows good results even for the finger print images which are printed not clearly and does not need to preprocess the images. It also shows good results for parallel displacement of fingerprint. The experiment result shows the effectiveness of the proposed algorithm.

• Speech Sciences
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• v.11 no.3
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• pp.131-142
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• 2004

Speaker identification system basically functions by comparing spectral energy of an individual production model with that of an input signal. This study aimed to develop a new speaker identification system from two parameters from the spectral energy of numeric sounds: difference sum and correlation coefficient. A narrow-band spectrogram yielded more stable spectral energy across time than a wide-band one. In this paper, we collected empirical data from four male speakers and tested the speaker identification system. The subjects produced 18 combinations of three-digit numeric. sounds !en times each. Five productions of each three-digit number were statistically averaged to make a model for each speaker. Then, the remaining five productions were tested on the system. Results showed that when the threshold for the absolute difference sum was set to 1200, all the speakers could not pass the system while everybody could pass if set to 2800. The minimum correlation coefficient to allow all to pass was 0.82 while the coefficient of 0.95 rejected all. Thus, both threshold levels can be adjusted to the need of speaker identification system, which is desirable for further study.

• The Journal of Internal Korean Medicine
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• v.41 no.6
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• pp.1052-1065
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• 2020

Objectives: To evaluate the reliability of a pattern identification tool for benign prostatic hyperplasia and to examine the relationship between pattern identification tool readings and IPSS and uroflowmetry. Methods: We analyzed 56 patients diagnosed with benign prostatic hyperplasia from December 27th, 2017 to December 26th, 2018 by two different Korean medical doctors and followed with a pattern identification tool and by IPSS and uroflowmetry. One week later, the patients were retested to analyze the reliability of the pattern identification tool, determined with the intraclass correlation coefficient (ICC) using the test-retest method. The correlation between IPSS and uroflowmetry was analyzed with the Pearson coefficient. Result: The reliability of the pattern identification tool for benign prostatic hyperplasia was evaluated as "poor agreement beyond chance" (ICC=0.349). The reliability of each pattern identification score was evaluated as "good" for Yang Deficiency of Kidney, Yin Deficiency of Kidney, Deficiency of Middle Qi, and Dampness-heat of Lower Energizer. The internal consistency was evaluated as "good" for Yang Deficiency of Kidney, Yin Deficiency of Kidney, and Dampness-heat of Lower Energizer, and as "excellent" for Deficiency of Middle Qi. The correlation between pattern identification and IPSS was evaluated as a "moderate positive correlation" for all pattern identifications. The average flow rate and maximum flow rate using uroflowmetry was evaluated with "moderate negative correlation" for Yang Deficiency of Kidney and Dampness-heat of Lower Energizer. Conclusion: The reliability of a pattern identification tool for benign prostatic hyperplasia was evaluated as "poor agreement beyond chance." Further research is needed.

• Journal of Physiology & Pathology in Korean Medicine
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• v.34 no.3
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• pp.142-148
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• 2020

The purpose of this study was to evaluate the validity of Deficiency and Excess Pattern Identification Questionnaire. The number of subjects enrolled in this study was 431. Pearson Correlation Coefficient analysis were conducted to reveal the correlation among Deficiency and Excess Pattern Identification Questionnaire, Grip Strength and Quality of life. ROC-curve analysis were used to suggest optimal cut off value. Cohen Kappa also used to analyze for diagnostic validity. The significant p-value was < .05. The Deficiency questionnaire had positive correlation with the score of the expert and negative correlation with Grip Strength and Quality of life (p<.001). The Excess questionnaire had positive correlation with the score of the expert and negative correlation with Quality of life (p<.001). The optimal cut off value was 56.5 to separate deficiency and non deficiency and 47.5 to separate excess and non-excess. Furthermore, AUC was .900 and .851 accordingly. Cohen Kappa value between deficiency questionnaire and the expert was .640. Cohen Kappa value between excess questionnaire and the expert was .513. This study reveals that Deficiency and Excess Pattern Identification Questionnaire is valid. However, further study considering of gender, age, and health condition and so on, is needed.

• Journal of Physiology & Pathology in Korean Medicine
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• v.32 no.6
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• pp.370-374
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• 2018

Oriental Diagnosis System(ODS) is an artificial intelligence program that utilize entered diagnosis knowledge, determine patient's disease and decide right medicine. The purpose of this study is to find a correlation between pattern Identification in Korean medicine and each sasang types(Tae-Eum and So-Yang) by analyzing ODS diagnosis result. Eventually our study secure availability of using ODS program at clinical training or developing diagnosis program. Subject of this study is 50 patients who was performed Sasang constitution diagnosis (28 patients were Tae-Eum and 22 patients were So-Yang). We analyize patient's diagnosis records by using ODS program and obtained result about pattern Identification. We used SPSS statistics 23 in analyzing the differences of the scores of Eight Principle Pattern Identification, Qi-Blood Pattern Identification, and Bing-xie Pattern Identification in each Sasang types (Tae-Eum, So-Yang). The Heat and Heat-moisture scores were significantly different(p<0.05) and Qi-Blood Pattern Identification scores were not different in each Sasang types(p>0.05). And Weight was significantly different in each Sasang types(p<0.05). It is hard to generalize the result because subject of this study was not enough and had sample speciality(tinnitus patients). However, we explained correlation between pattern Identification in korean medicine and each sasang types based on quantifiable and objective evidence system. it can be used at education of korean medicine and evidence of practice diagnosis. Futhermore, there have been no studies about anaylizing correlation between pattern Identification in Korean medicine and each sasang types using ODS program. So it is worthy of being utilized at clinical evidence data of ODS program.

• Journal of Institute of Control, Robotics and Systems
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• v.6 no.5
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• pp.390-395
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• 2000

We present a fingerprint identification algorithm using the wavelet transform and correlation. The wavelet transform is used because of its simple operation to extract fingerprint minutiaes features for fingerprint classification. We perform the rowwise 1-D wavelet transform for a $256\times256$ fingerprint image to get a $1\times256$ column vector using the Haar wavelet and repeat 1-D wavelet transform for a 1$\times$256 column vector to get a $1\times4$ feature vector. Using PNN(Probabilistic Neural Network), we select the possible candidates from the stored feature vectors for fingerprint images. For those candidates, we compute the correlation between the input binary image and the target binary image to find the most similar fingerprint image. The proposed algorithm may be the key to a low cost fingerprint identification system that can be operated on a small computer because it does not need a large memory size and much computation.