• The Transactions of The Korean Institute of Electrical Engineers
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• v.64 no.9
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• pp.1337-1346
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• 2015

In this paper, pattern classifier is designed to classify precipitation and non-precipitation events from weather radar data. The proposed classifier is based on Fuzzy Neural Network(FNN) and consists of three FNNs which operate in parallel. In the proposed network, the connection weights of the consequent part of fuzzy rules are expressed as two polynomial types such as constant or linear polynomial function, and their coefficients are learned by using Least Square Estimation(LSE). In addition, parametric as well as structural factors of the proposed classifier are optimized through Differential Evolution(DE) algorithm. After event classification between precipitation and non-precipitation echo, non-precipitation event is to get rid of all echo, while precipitation event including non-precipitation echo is to get rid of non-precipitation echo by classifier that is also based on Fuzzy Neural Network. Weather radar data obtained from meteorological office is to analysis and discuss performance of the proposed event and echo patter classifier, result of echo pattern classifier compare to QC(Quality Control) data obtained from meteorological office.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.1
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• pp.169-177
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• 2020

In South Korea, the results of R&D in science and technology are submitted to the National Science and Technology Information Service (NTIS) in reports that have Korea national science and technology standard classification codes (K-NSCC). However, considering there are more than 2000 sub-categories, it is non-trivial to choose correct classification codes without a clear understanding of the K-NSCC. In addition, there are few cases of automatic document classification research based on the K-NSCC, and there are no training data in the public domain. To the best of our knowledge, this study is the first attempt to build a highly performing K-NSCC classification system based on NTIS report meta-information from the last five years (2013-2017). To this end, about 210 mid-level categories were selected, and we conducted preprocessing considering the characteristics of research report metadata. More specifically, we propose a convolutional neural network (CNN) technique using only task names and keywords, which are the most influential fields. The proposed model is compared with several machine learning methods (e.g., the linear support vector classifier, CNN, gated recurrent unit, etc.) that show good performance in text classification, and that have a performance advantage of 1% to 7% based on a top-three F1 score.

• Journal of the Korean Mathematical Society
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• v.54 no.5
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• pp.1537-1556
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• 2017

In this paper, we introduce the notion of generating index ${\mathcal{I}}_1(A)$ (2-generating index ${\mathcal{I}}_2(A)$, resp.) of a left-symmetric algebra A, which is the maximum of the dimensions of the subalgebras generated by any element (any two elements, resp.). We give a classification of left-symmetric algebras with ${\mathcal{I}}_1(A)=1$ and ${\mathcal{I}}_2(A)=2$, 3 resp., and show that all such algebras can be constructed by linear and bilinear functions. Such algebras can be regarded as a generalization of those relating to the integrable (generalized) Burgers equation.

• Food Science of Animal Resources
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• v.29 no.1
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• pp.132-139
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• 2009

The objective of this study was to investigate the most effective analysis methods for palatability grading of Hanwoo beef by comparing the results of discriminant analysis with sensory data. The sensory data were obtained from sensory testing by 1,300 consumers evaluated tenderness, juiciness, flavor-likeness and overall acceptability of Hanwoo beef samples prepared by boiling, roasting and grilling cooking methods. For the discriminant analysis with one factor, overall acceptability, the linear discriminant functions and the non-parametric discriminant function with the Gaussian kernel were estimated. The linear discriminant functions were simple and easy to understand while the non-parametric discriminant functions were not explicit and had the problem of selection of kernel function and bandwidth. With the three palatability factors such as tenderness, juiciness and flavor-likeness, the canonical discriminant analysis was used and the ability of classification was calculated with the accurate classification rate and the error rate. The canonical discriminant analysis did not need the specific distributional assumptions and only used the principal component and canonical correlation. Also, it contained the function of 3 factors (tenderness, juiciness and flavor-likeness) and accurate classification rate was similar with the other discriminant methods. Therefore, the canonical discriminant analysis was the most proper method to analyze the palatability grading of Hanwoo beef.

• Journal of the Korean Chemical Society
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• v.36 no.1
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• pp.113-124
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• 1992

The pattern recognition methods of chemometrics have been applied to multivariate data, for which ninety four Korean ancient glass pieces have been determined for 12 elements by neutron activation analysis. For the purpose, principal component analysis and non-linear mapping have been used as the unsupervised learning methods. As the result, the glass samples have been classified into 6 classes. The SIMCA (statistical isolinear multiple component analysis), adopted as a supervised learning method, has been applied to the 6 training set and the test set. The results of the 6 training set were in accord with the results by principal component analysis and non-linear mapping. For test set, 17 of 33 samples were each allocated to one of the 6 training set.

• Journal of the Society of Naval Architects of Korea
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• v.43 no.2 s.146
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• pp.197-205
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• 2006

In general, brackets found at tank boundary are design according to the Classification Society Rule. Since much man power is needed in manufacturing the brackets stiffened by flange, it is necessary to suggest alternative designs, of which flanges are removed, through the rigorous structural analysis. In this paper non-linear structural analysis for brackets with and/or without flange have been carried out to examine their structural behavior and ultimate strengths. Alternative designs for brackets are suggested based on the results of ultimate strength analysis so that the alternative brackets have the similar level of strength and stiffness to the original brackets. It has been seen that the structural safety of alternative brackets proposed in this paper are beyond the appropriate level. The primary benefit of replacing the original brackets by the alternatives is the reduction of man power in manufacturing brackets and 10 to 15% weight saving can be expected in additional. This paper ends with some comments about the extension of the present study.

• Archives of Plastic Surgery
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• v.38 no.2
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• pp.143-147
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• 2011

Purpose: A Tessier classification number 7 cleft is an uncommon malformation that results from a failure of mesenchymal fusion within the maxillary and mandibular prominences of the 1st pharyngeal arch. Many operative techniques of the number 7 cleft repair have been proposed to restore function and improve aesthetics. Fifteen patients underwent repair of a number 7 cleft over 13 years by a modification of the surgical Technique, and an appraisal of the operative outcome is reported herein. Methods: A retrospective review was conducted involving 15 patients with number 7 clefts who underwent surgery from 1996 to 2009. The changes in surgical technique included skin closure, attachment of the orbicularis oris muscle, and position of the repaired commissure; the changes were analysed with a review of the medical records and the outcomes of surgery were analysed via photographs. Specifically, the technique of skin closure was changed from the a Z-plasty to a linear closure, the orbicularis oris muscle overlapped attachment was replaced by a side-to-side approximation with horizontal mattress sutures, and the position of the repaired commissure was changed from 1 mm laterally to 1 mm medially in reference to the non-cleft side. Results: A Z-plasty caused additional cutaneous scarring, an overlapped attachment of the orbicularis oris muscle caused a thick oral commissure, and the repaired commissure migrated to the lateral side, so a 1 mm, laterally-positioned commissure caused asymmetry. The altered procedure included a linear skin closure, a side-to-side orbicularis oris muscle approximation, and a 1 mm, medially-positioned commissure, which together resulted in a good outcome. Conclusion: The altered procedure for repair of a number 7 cleft as described herein, yields a short scar, no functional problems with the orbicularis oris muscle, a thin oral commissure, and symmetry of the repaired commissure.

• Journal of Biomedical Engineering Research
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• v.37 no.4
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• pp.127-133
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• 2016

This study proposes the feasibility for automatic classification of sleep/wakefulness using nasal pressure in patients with sleep-disordered breathing (SDB). First, SDB events were detected using the methods developed in our previous studies. In epochs for normal breathing, we extracted the features for classifying sleep/wakefulness based on time-domain, frequency-domain and non-linear analysis. And then, we conducted the independent two-sample t-test and calculated Mahalanobis distance (MD) between the two categories. As a results, $SD_{LEN}$ (MD = 0.84, p < 0.01), $P_{HF}$ (MD = 0.81, p < 0.01), $SD_{AMP}$ (MD = 0.76, p = 0.031) and $MEAN_{AMP}$ (MD = 0.75, p = 0.027) were selected as optimal feature. We classified sleep/wakefulness based on support vector machine (SVM). The classification results showed mean of sensitivity (Sen.), specificity (Spc.) and accuracy (Acc.) of 60.5%, 89.0% and 84.8% respectively. This method showed the possibilities to automatically classify sleep/wakefulness only using nasal pressure.

• Journal of the Korean Society of Safety
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• v.33 no.4
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• pp.21-29
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• 2018

In many companies handling flammable liquids, explosion-proof electrical equipment have been installed according to the Korean Industrial Standards (KS C IEC 60079-10-1). In these standards, hazardous area for explosive gas atmospheres has to be classified by the evaluation of the evaporation rate of flammable liquid leakage. The evaporation rate is an important factor to determine the zones classification and hazardous area distance. However, there is no systematic method or rule for the estimation of evaporation rate in these standards and the first principle equations of a evaporation rate are very difficult. Thus, it is really hard for industrial workplaces to employ these equations. Thus, this problem can trigger inaccurate results for evaluating evaporation range. In this study, empirical models for estimating an evaporation rate of flammable liquid have been developed to tackle this problem. Throughout the sensitivity analysis of the first principle equations, it can be found that main factors for the evaporation rate are wind speed and temperature and empirical models have to be nonlinear. Polynomial regression is employed to build empirical models. Methanol, benzene, para-xylene and toluene are selected as case studies to verify the accuracy of empirical models.

• Journal of Information Processing Systems
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• v.1 no.1 s.1
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• pp.22-26
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• 2005

In this paper, we classified the objectionable texts into four rates according to their harmfulness and proposed the hierarchical text rating system for objectionable documents. Since the documents in the same category have similarities in used words, expressions and structure of the document, the text rating system, which uses a single classification model, has low accuracy. To solve this problem, we separate objectionable documents into several subsets by using their properties, and then classify the subsets hierarchically. The proposed system consists of three layers. In each layer, we select features using the chi-square statistics, and then the weight of the features, which is calculated by using the TF-IDF weighting scheme, is used as an input of the non-linear SVM classifier. By means of a hierarchical scheme using the different features and the different number of features in each layer, we can characterize the objectionability of documents more effectively and expect to improve the performance of the rating system. We compared the performance of the proposed system and performance of several text rating systems and experimental results show that the proposed system can archive an excellent classification performance.