• Health Policy and Management
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• v.22 no.4
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• pp.522-537
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• 2012

The purpose of this study was to analyze the level of the cognitive function and activities of daily living of the beneficiary older adults at home based on Korean Long-term Care Insurance System. A cross-sectional descriptive survey was conducted from November 2010 to May 2011, the final respondents were 1,026 beneficiary older adults taking home visit care covered in Korean long-term care insurance system. The questionnaire included general characteristics of subjects, cognitive function, ADL(Activity of daily living). The data was analyzed using the SPSS 20.0 version. There was significant difference in cognitive function and ADL between 1st Grade, 2nd Grade and 3rd Grade of long-term care classification. The correlated factors of cognitive function were ADL, long-term care grade, disability of arm and leg, limitation of joint, bed sore and tube feeding. The correlated factors of ADL were cognitive function, long-term care grade, disability of arm and leg, bed sore and tube feeding. This study suggests that cognitive functions have to be mainly considered in long-term care grade. It is necessary to make an effort to develop long-term care grade in Korean long-term care insurance system an cognitive function improvement program for the beneficiary older adults. Above all things government will be seriously contemplating of revise contents for long-term care grade to provide quality of care for the older adults.

• Journal of Electrical Engineering and Technology
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• v.13 no.5
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• pp.2099-2106
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• 2018

This study presents a novel approach of discriminative feature vectors based on manifold learning using nonlinear dimension reduction (DR) technique to improve loss function, and combine with the Adversarial examples to regularize the object function for image classification. The traditional convolutional neural networks (CNN) with many new regularization approach has been successfully used for image classification tasks, and it achieved good results, hence it costs a lot of Calculated spacing and timing. Significantly, distrinct from traditional CNN, we discriminate the feature vectors for objects without empirically-tuned parameter, these Discriminative features intend to remain the lower-dimensional relationship corresponding high-dimension manifold after projecting the image feature vectors from high-dimension to lower-dimension, and we optimize the constrains of the preserving local features based on manifold, which narrow the mapped feature information from the same class and push different class away. Using Adversarial examples, improved loss function with additional regularization term intends to boost the Robustness and generalization of neural network. experimental results indicate that the approach based on discriminative feature of manifold learning is not only valid, but also more efficient in image classification tasks. Furthermore, the proposed approach achieves competitive classification performances for three benchmark datasets : MNIST, CIFAR-10, SVHN.

• Korean Journal of Clinical Pharmacy
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• v.15 no.2
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• pp.139-148
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• 2005

Appropriate drug classification is important fur rational drug consumption. This study was conducted to evaluate the appropriateness of current drug classification system and suggest possible ways for improving the system. Nonprescription drug market has been decreased. Since total 27,962 products had been classified (prescription 17,187 vs. nonprescription 10,775 products, 61.5% vs. 38.5%) in July 2000 for implementing separation of drug prescribing and dispensing system, there are no classification changes. Reclassification is not motivated by product holder and regulatory system did not lead classification change either. Consumers' ease access to some nonprescription drugs is demanded. But point of public awareness and cultural and health environmental views, saff drug use rather than advantages from broad supply of nonprescription drugs is more critical. We concluded that current 2-categorized (prescription and nonprescription) drug classification system is appropriate, and addition of general sale category should be approached carefully with long term Preparations such as establishment of better nonprescription drug consuming infrastructure by public information provision and education for improving public medicinal knowledge and strengthening self medication guidance, and review of current classification status of marketed drugs and switching possibilities. For systemizing and encouraging reclassification, introduction of regulatory renewal system as a continuous reevaluation program which is the best way to review appropriateness of drug classification as well as provision of detailed guidance for industry including policy, requirement and process fer reclassification application, are necessary.

• Proceedings of the KSRS Conference
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• 2002.10a
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• pp.441-441
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• 2002

In order to ensure a balance between economic development and a healthy Mekong Basin environment supporting natural resources diversity and productivity critical to the livelihood of its 65 million inhabitants, the Mekong River Commission (MRC) has been investigating the use of radar to remotely characterize and monitor the diversity, complexity, size and connectivity of the Basin's aquatic habitats. The PACRIM AIRSAR Mission provided an opportunity to evaluate the usefulness of radar technology to derive information for assessing, forecasting and mitigating possible cumulative and long-term impacts of development on the natural environment and the people's livelihood. This paper presents the results of mapping wetland cover types using multi-polarimetric radar for an area of the north-western corner of the Tonle Sap basin with data acquired from the AIRSAR Mission in September 2000. The implementation of a newly developed segmentation classification routine used to derive the image classification is described and the results of a fieldwork campaign to check the classification is presented.

• Journal of applied mathematics & informatics
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• v.14 no.1_2
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• pp.237-249
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• 2004

Consider the second order self-adjoint neutral difference equation of form $\Delta(a_n$\mid$\Delta(x_n\;-\;{p_n}{x_{{\tau}_n}}$\mid$^{\alpha}sgn{\Delta}(x_n\;-\;{p_n}{x_{{\tau}_n}}\;+\;f(n,\;{x_{g_n}}\;=\;0$. In this paper, we will give the classification of nonoscillatory solutions of the above equation; and by the fixed point theorem, we present some existence results for some kinds of nonoscillatory solutions of the equation.

• International Journal of Contents
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• v.1 no.2
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• pp.26-30
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• 2005

According to the fast growth of information on the Internet, it is becoming increasingly difficult to find and organize useful information. To reduce information overload, it needs to exploit automatic text classification for handling enormous documents. Support Vector Machine (SVM) is a model that is calculated as a weighted sum of kernel function outputs. This paper describes a document classifier for web documents in the fields of Information Technology and uses SVM to learn a model, which is constructed from the training sets and its representative terms. The basic idea is to exploit the representative terms meaning distribution in coherent thematic texts of each category by simple statistics methods. Vector-space model is applied to represent documents in the categories by using feature selection scheme based on TFiDF. We apply a category factor which represents effects in category of any term to the feature selection. Experiments show the results of categorization and the correlation of vector length.

• Journal of the Korean Institute of Intelligent Systems
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• v.19 no.2
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• pp.212-217
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• 2009

There are rule-based learning method and statistic based learning method and so on which represent learning method for hierarchy relation between domain term. In this paper, we propose to leveling and similarity measure using the extended AHP of fuzzy term in Information system. In the proposed method, we extract fuzzy term in document and categorize ontology structure about it and level priority of fuzzy term using the extended AHP for specificity of fuzzy term. the extended AHP integrates multiple decision-maker for weighted value and relative importance of fuzzy term. and compute semantic similarity of fuzzy term using min operation of fuzzy set, dice's coefficient and Min+dice's coefficient method. and determine final alternative fuzzy term. after that compare with three similarity measure. we can see the fact that the proposed method is more definite than classification performance of the conventional methods and will apply in Natural language processing field.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.12 no.4
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• pp.277-284
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• 2012

Named entity recognition (NER) technique can play a crucial role in extracting information from the web. While NER systems with relatively high performances have been developed based on careful manipulation of terms with a statistical model, term mismatches often degrade the performance of such systems because the strings of all the candidate entities are not known a priori. Despite the importance of lexical-level term mismatches for NER systems, however, most NER approaches developed to date utilize only the term string itself and simple term-level features, and do not exploit the semantic features of terms which can handle the variations of terms effectively. As a solution to this problem, here we propose to match the semantic concepts of term units in restaurant named entities (NEs), where these units are automatically generated from multiple resolutions of a semantic tree. As a test experiment, we applied our restaurant NER scheme to 49,153 nouns in Korean restaurant web pages. Our scheme achieved an average accuracy of 87.89% when applied to test data, which was considerably better than the 78.70% accuracy obtained using the baseline system.

• Journal of Environmental Impact Assessment
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• v.5 no.1
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• pp.95-105
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• 1996

Meteorological Joint Frequency Function required indispensably in long-term air quality prediction models were discussed for practical application in Korea. The algorithm, proposed by Turner(l964), is processed with daily solar insolation and cloudiness and height basically using Pasquill's atmospheric stability classification method. In spite of its necessity and applicability, the computer program, called STAR(STability ARray), had some significant difficulties caused from the difference in meteorological data format between that of original U.S. version and Korean's. To cope with the problems, revised STAR program for Korean users were composed of followings; applicability in any site of Korea with regard to local solar angle modification; feasibility with both of data which observed by two classes of weather service centers; and examination on output format associated with prediction models which should be used.

• Journal of Environmental Impact Assessment
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• v.16 no.2
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• pp.157-168
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• 2007

In case there is a need to run the multi-year urban scale air qulaity model, it is a difficult task due to the computational demand, requiring the statistical approach for the long time atmospheric environmental assessment. In an effort to approach toward long term urban assessment, the sixteen synoptic meteorological conditions are statistically classified from the estimated geostrophic wind speeds and directions of 850 hPa geopotential height field during 2000 ~ 2005. The geostrophic wind directions are subdivided into four even intervals (north, east, south, and west), geostrophic wind speeds into two classes(${\leq}5m/s$ and >5m/s), and daily mean cloud amount into 2 classes(${\leq}5/10$ and >5/10), which result into sixteen classes of the synoptic meteorological cases for each season. The frequency distributions for each 16 synoptic meteorological case are examined and some discussions on how these synoptic classifications can be used in the environmental assessment are presented.