• Journal of the Korean Society for Library and Information Science
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• v.31 no.3
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• pp.7-22
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• 1997

Korean Library Association brought out the fourth revised and enlarged edition of KDC last year. Compared with the former edition It Is a marked improvement. Neverthless, it leaves much room for improvement. In order to examine and evaluate the edition more effectively, I confined my study to the class 'Philosophy'. In my judgment the problem resolves itself into following three points: 1) Each regions, blanches of philosophy is not properly balanced. As is generally known KDC was originally derived from DDC. As a result KDC and DBC are similiar with regard to their stress on the philosophical tradition of the West. In consequence, it is lacking in universality. 2) The classifiers neglected on several occassions the logical regulations of classification. The vertical and horizontal relations between the subjects are not strictly respected. 3) The persons concerned were not well informed of philosophical conceptions and genealogies. There are some misused conceptions and disorganized genealogies of philosophy. To my knowledge these problems originate in the lack of professional understanding of philosophy necessary to make the work satisfactory As a result of the examination I came to the conclusion that it is inevitable for the classifiers, to ask to specialists in philosophy for mutual cooperation. Without their professional advices the classifiers will find difficulty in solving the problems and in improving the classification

• Journal of the Korean Association of Oral and Maxillofacial Surgeons
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• v.28 no.3
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• pp.175-181
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• 2002

Intermaxillary fixation and occusal splint are routine procedure for maxillofacial fracture and orthognathic surgery. When these methods could obstruct oral airway the patients who kept intermaxillary fixation and occusal splint in their mouth, are very difficult to breath after surgery. Nasal bleeding and pharyngeal edema due to nasotracheal intubation, residual effect of muscle relaxants, and anesthetic agent could be contributing factor of airway obstruction. In this study, pulmonary function test was evaluated before and after intermaxillary fixation, and intermaxillary fixation with occusal splint in 22 volunteers. The results were as follows 1. FVC, %FVC, $FEV_1$, $FEV_1%$, PEF, $PEF_{50}$, MVV without intermaxillary fixtion were 4.45L, 88%, 4.03L, 90.9%, 10.26L/s, 5.53L/s, and 136.14L/min, and with intermaxillary fixation were 3.51L, 68.67%, 3.06L, 69.39L, 6.52L/s, 3.94L/s, and 69.39L/min. The results with intermaxillary fixation and occusal splint were 2.15L, 42.41%, 1.71L, 38.81%, 2.83L/s, 1.74L/s, and 37.14L/min. 2. Compared with before and after intermaxillary fixation, all values of pulmonary function test were decreased and after intermaxillary fixation and intermaixillary fixation with occulasal splint, the results were decreased. 3. MVV and PEF were decreased significantly with interaxillary fixtion and occusal splint, and FVC was less decreased. It meant that intermaxillary fixation and occluasal splint induced reduction of respiratory flow significantly, but less reduction of respiratory volume. 4. Intermaxillary fixation and occulsal splint induced increase of airway resistance, decrease of expiratory volume and air flow. So severe respiratory difficulty could be seen to all volunteers who kept intermaxillary fixtion and occusal splint. 5. In classification of respiratory difficulty, intermaxillary fixation with occulsal splint induced complex respiratory difficulty more than intermaxillary fixation only did. From the above results, doctors who care patients kept intermaxillary fixation and occusal splint should be aware of respiratory depression caused by these treatment.

• Journal of Biomedical Engineering Research
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• v.31 no.6
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• pp.456-463
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• 2010

In the present study, we proposed a new subspace scanning algorithm to enhance the spatial resolution of electroencephalography (EEG) and magnetoencephalography(MEG) source localization. Subspace scanning algorithms, represented by the multiple signal classification (MUSIC) algorithm and the first principal vector (FINE) algorithm, have been widely used to localize asynchronous multiple dipolar sources in human cerebral cortex. The conventional MUSIC algorithm used principal component analysis (PCA) to extract the noise vector subspace, thereby having difficulty in discriminating two or more closely-spaced cortical sources. The FINE algorithm addressed the problem by using only a part of the noise vector subspace, but there was no golden rule to determine the number of noise vectors. In the present work, we estimated a non-orthogonal signal vector set using independent component analysis (ICA) instead of using PCA and performed the source scanning process in the signal vector subspace, not in the noise vector subspace. Realistic 2D and 3D computer simulations, which compared the spatial resolutions of various algorithms under different noise levels, showed that the proposed ICA-MUSIC algorithm has the highest spatial resolution, suggesting that it can be a useful tool for practical EEG/MEG source localization.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.10a
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• pp.34-36
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• 2022

In the existing text sentiment analysis models, the entire text is usually directly modeled as a whole, and the hierarchical relationship between text contents is less considered. However, in the practice of sentiment analysis, many texts are mixed with multiple emotions. If the semantic modeling of the whole is directly performed, it may increase the difficulty of the sentiment analysis model to judge the sentiment, making the model difficult to apply to the classification of mixed-sentiment sentences. Therefore, this paper proposes a sentiment analysis model BHGCN that considers the text hierarchy. In this model, the output of hidden states of each layer of BERT is used as a node, and a directed connection is made between the upper and lower layers to construct a graph network with a semantic hierarchy. The model not only pays attention to layer-by-layer semantics, but also pays attention to hierarchical relationships. Suitable for handling mixed sentiment classification tasks. The comparative experimental results show that the BHGCN model exhibits obvious competitive advantages.

• The Journal of the Korea Contents Association
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• v.5 no.4
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• pp.150-159
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• 2005

With the increase of interest in ubiquitous computing, image code is attracting attention in various areas. Image code is important in ubiquitous computing in that it can complement or replace RFID (radio frequency identification) in quite a few areas as well as it is more economical. However, because of the difficulty in reading precise colors due to the severe distortion of colors, its application is quite restricted by far. In this paper, we present an efficient method of image code recognition including automatically locating the image code using the hue and saturation values. In our experiments, we use an image code whose design seems most practical among currently commercialized ones. This image code uses six safe colors, i.e., R, G, B, C, M, and Y. We tested for 72 true-color field images with the size of $2464{\times}1632$ pixels. With the color calibration based on the histogram, the localization accuracy was about 96%, and the accuracy of color classification for localized codes was about 91.28%. It took approximately 5 seconds to locate and recognize the image code on a PC with 2 GHz P4 CPU.

• Journal of the Korean Data and Information Science Society
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• v.22 no.4
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• pp.671-678
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• 2011

Data mining searches for interesting relationships among items in a given database. The methods of data mining are decision tree, association rules, clustering, neural network and so on. The decision tree approach is most useful in classification problems and to divide the search space into rectangular regions. Decision tree algorithms are used extensively for data mining in many domains such as retail target marketing, customer classification, etc. When create decision tree model, complicated model by standard of model creation and number of input variable is produced. Specially, there is difficulty in model creation and analysis in case of there are a lot of numbers of input variable. In this study, we study on decision tree using intervening variable. We apply to actuality data to suggest method that remove unnecessary input variable for created model and search the efficiency.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.29 no.6
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• pp.1235-1242
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• 2019

While several machine learning technique has been implemented for Android malware categorization, there is still difficulty in analyzing due to overfitting problem and including of un-executable code, etc. In this paper, we introduce our implemented tool to address these problems. Tool is consists of approximately 1,500 lines of Java code, and perform Flow analysis on set of APIs, or on control flow graph. Our tool groups all the API by its relationship and only perform analysis on actually executing code. Using our tool, we grouped 39032 APIs into 4972 groups, and 12123 groups with result of including class names. We collected 7,000 APKs from 7 families and evaluated our feature reduction technique, and we also reduced features again with selecting APIs that have frequency more than 20%. We finally reduced features to 263-numbers of feature for our collected APKs.

• Journal of the Korean School Mathematics Society
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• v.16 no.3
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• pp.561-582
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• 2013

Meanwhile, the meaning has been emphasized in mathematics. But the meaning of meaning had not been clearly defined and the meaning classification had not been reported. In this respect, the meaning was classified as expressive and cognitive. Furthermore, it was reclassified as mathematical situation and real situation. Based on this classification, we investigated how student recognizes the meaning when solving mathematical modeling problem. As a result, we found that the understanding of cognitive meaning in real situation is more difficult than that of the other meaning. And we knew that understanding the meaning in solving of equation, has more difficulty than in expression of equation. Thus, to help students understanding the meaning in the whole process of mathematical modeling, we have to connect real situation with mathematical situation. And this teaching method through unit and measurement, will be an alternative method for connecting real situation and mathematical situation.

• The Korean Journal of Applied Statistics
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• v.35 no.1
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• pp.131-146
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• 2022

Logit models are commonly used to predicting and classifying categorical response variables. Most Bayesian approaches to logit models are implemented based on the Metropolis-Hastings algorithm. However, the algorithm has disadvantages of slow convergence and difficulty in ensuring adequacy for the proposal distribution. Therefore, we use auxiliary mixture sampler proposed by Frühwirth-Schnatter and Frühwirth (2007) to estimate logit models. This method introduces two sequences of auxiliary latent variables to make logit models satisfy normality and linearity. As a result, the method leads that logit model can be easily implemented by Gibbs sampling. We applied the proposed method to diabetes data from the Community Health Survey (2020) of the Korea Disease Control and Prevention Agency and compared performance with Metropolis-Hastings algorithm. In addition, we showed that the logit model using auxiliary mixture sampling has a great classification performance comparable to that of the machine learning models.

• KIPS Transactions on Software and Data Engineering
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• v.7 no.12
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• pp.477-484
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• 2018

Due to the advancement of computer and information technologies, numerous papers have been published. As new research fields continue to be created, users have a lot of trouble finding and categorizing their interesting papers. In order to alleviate users' this difficulty, this paper presents a method of grouping similar papers and clustering them. The presented method extracts primary keywords from the abstracts of each paper by using TF-IDF. Based on TF-IDF values extracted using K-means clustering algorithm, our method clusters papers to the ones that have similar contents. To demonstrate the practicality of the proposed method, we use paper data in FGCS journal as actual data. Based on these data, we derive the number of clusters using Elbow scheme and show clustering performance using Silhouette scheme.