• Proceedings of the KIEE Conference
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• 1995.07b
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• pp.910-912
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• 1995

This paper proposes an effective algorithm for automatic classification of power quality disturbances(PQD), where wavelet theory is utilized for the detection of PQD, and three neural networks such as MLP, RBF, MLP-Class are combined in parallel to classify PQD. To demonstrate the performance of the proposed system, simulation results are provided.

• Communications of the Korean Mathematical Society
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• v.9 no.4
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• pp.951-959
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• 1994

A sequence ${X_j : j \geq 1}$ of random variables is said to be pairwise positive quadrant dependent (pairwise PQD) if for any real $r-i,r_j$ and $i \neq j$ $$ P{X_i > r_i,X_j > r_j} \geq P{X_i > r_i}P{X_j > r_j} $$ (see [8]) and a sequence ${X_j : j \geq 1}$ of random variables is said to be associated if for any finite collection ${X_{i(1)},...,X_{j(n)}}$ and any real coordinatewise nondecreasing functions f,g on $R^n$ $$ Cov(f(X_{i(1)},...,X_{j(n)}),g(X_{j(1)},...,X_{j(n)})) \geq 0, $$ whenever the covariance is defined (see [6]). Instead of association Cox and Grimmett's [4] original central limit theorem requires only that positively linear combination of random variables are PQD (cf. Theorem $A^*$).

• Journal of Biomedical Engineering Research
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• v.44 no.2
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• pp.118-124
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• 2023

Many recent studies have reported that the quality of input learning data was vital to the detection of regions of interest. However, due to a lack of research on the quality of learning data on lesion detetcting using gastroscopy, we aimed to quantify the impact of quality difference in endoscopic images to lesion detection models using Image Quality Assessment (IQA) algorithms. Through IQA methods such as BRISQUE (Blind/Referenceless Image Spatial Quality Evaluation), Laplacian Score, and PSNR (Peak Signal-To-Noise) algorithm on 430 sheets of high quality data (HQD) and 430 sheets of low quality data (PQD), we showed that there were significant differences between high and low quality images in lesion detecting through BRISQUE and Laplacian scores (p<0.05). The PSNR value showed 10.62±1.76 dB on average, illustrating the lower lesion detection performance of PQD than HQD. In addition, F1-Score of HQD showed higher detection performance at 77.42±3.36% while F1-Score of PQD showed 66.82±9.07%. Through this study, we hope to contribute to future gastroscopy lesion detection assistance systems that involve IQA algorithms by emphasizing the importance of using high quality data over lower quality data.

• Communications for Statistical Applications and Methods
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• v.3 no.3
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• pp.235-245
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• 1996

In this paper, a partial ordering of positive quadrant dependence(PQD) for bivariate stochastic processes are introduced and basic properties and closure under certain statistical operations are derived. Examples are given to illustrate these concepts

• Journal of applied mathematics & informatics
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• v.6 no.3
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• pp.959-968
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• 1999

In this paper we are obtained new results for bivariate pro-cesses which help us to tell the dependent structure among hitting times of the processes. We are proposed both dependence properties and the-oretical results among the processes and certain kinds of dependence properties when we are imposed on processes are reflected as analo-gous properties of corresponding hitting times. Finlly we are given some examples to illustrate these concepts.

• Journal of applied mathematics & informatics
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• v.5 no.2
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• pp.553-564
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• 1998

In this paper we introduce a new concept of more weakly quadrant dependence of hitting times of stochastic processes. This concept is weaker than the more positively quadrant dependence of hitting times of stochastic processes. This concept is weaker than the more positively quadrant dependence and it is closed under some statistical operations of weakly positive quadrant dependence(WPQD) ordering.

• The Journal of the Korea institute of electronic communication sciences
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• v.18 no.1
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• pp.115-126
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• 2023

Due to the fluctuating random and periodical nature of renewable energy generation power quality disturbances occurred more frequently in power generation transformation transmission and distribution. Various power quality disturbances may lead to equipment damage or even power outages. Therefore it is essential to detect and classify different power quality disturbances in real time automatically. The traditional PQD identification method consists of three steps: feature extraction feature selection and classification. However, the handcrafted features are imprecise in the feature selection stage, resulting in low classification accuracy. This paper proposes a deep neural architecture based on Convolution Neural Network and Long Short Term Memory combining the time and frequency domain features to recognize 16 types of Power Quality signals. The frequency-domain data were obtained from the Fast Fourier Transform which could efficiently extract the frequency-domain features. The performance in synthetic data and real 6kV power system data indicate that our proposed method generalizes well compared with other deep learning methods.

• Journal of the Korean Mathematical Society
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• v.36 no.2
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• pp.381-402
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• 1999

Let {Rn($\chi$)}{{{{ { } atop {n=0} }}}} be a discrete Sobolev orthogonal polynomials (DSOPS) relative to a symmetric bilinear form (p,q)={{{{ INT _{ } }}}} pqd$\mu$0 +{{{{ INT _{ } }}}} p qd$\mu$1, where d$\mu$0 and d$\mu$1 are signed Borel measures on . We find necessary and sufficient conditions for {Rn($\chi$)}{{{{ { } atop {n=0} }}}} to satisfy a second order difference equation 2($\chi$) y($\chi$)+ 1($\chi$) y($\chi$)= ny($\chi$) and classify all such {Rn($\chi$)}{{{{ { } atop {n=0} }}}}. Here, and are forward and backward difference operators defined by f($\chi$) = f($\chi$+1) - f($\chi$) and f($\chi$) = f($\chi$) - f($\chi$-1).

• Journal of Nutrition and Health
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• v.36 no.5
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• pp.515-527
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• 2003

Objectives： A meta-analysis of the literatures was conducted to evaluate the cost-effectiveness of medical nutrition therapy by dietitians. Methods : The 30 studies were identified from a computerized search of published research on MEDLINE, Science-Direct and the PQD database until May, 2002 and a review of reference lists. The main search terms were“dietitian”,“dietary intervention”,“nutrition intervention”, “cost”,“cost-effectiveness”and“cost-benefit analysis”. The subgroup analysis was performed by publication year, study design, intervention provider, type of patient (in/out-patient) and type of cost (total cost/direct cost). Two reviewers independently selected trials for inclusion, assessed the quality and extracted the data. Results : The 30 studies were identified using the electric database search and bibliographies. The 17 trials were eligible for inclusion criteria, then the systematic review and a meta-analysis were conducted on effectiveness and cost-effectiveness of medical nutrition therapy. The quality of the studies was evaluated using the quality assessment tool for observational studies. The quality score was 0.515 $\pm$ 0.121 (range : 0.279-0.711, median : 0.466). The meta-analysis of 17 studies based on the random effect model showed that medical nutrition therapy was highly effective in treating the diseases (effect size 0.3092 : 95% confidence interval 0.2282-0.3303). The vote-counting method, one of meta-analysis methods, was applied to evaluate the cost-effectiveness of medical nutrition therapy conducted by dietitians. Two criteria (method 1, method 2) for voting were used. The calculated p-values for method 1 (more conservative method) and method 2 (less conservative method) were 0.1250 and 0.0106, respectively. Medical nutrition therapy by dietitians was significantly cost-effective in the method 2. Conclusion. This meta-analysis showed that the effectiveness of medical nutrition therapy was statistically significant in treating disease (effect size 0.3092), and that the cost-effectiveness of medical nutrition therapy was statistically significant in the method 2 (less conservative method) of vote counting. (Korean J Nutrition 36(5): 515~527, 2003)