• Journal of the Korean Society for information Management
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• v.20 no.1
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• pp.457-488
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• 2003

Public records, produced during the period of Government-General of Chosun. are essential sources for Korean modern history research. The purpose of this study is to provide a guideline for developing function-based classification scheme for the records. This present paper begins with analyzing archival principles regarding the function-based classification. and examines the problems of current arrangement practices. Based on these analyses, it suggests a guideline for constructing a classification system and a functional thesaurus for the public records of Government-General of Chosun. This guideline also covers functional analysis process and some considerations of different classification aspects which are conceptual, verbal and notational.

• Journal of the Korean Society of Physical Medicine
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• v.14 no.2
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• pp.97-105
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• 2019

PURPOSE: This study examined the factors related to school-based activity performance in school-aged children with spastic cerebral palsy (CP). METHODS: The Gross Motor Function Systems (GMFCS), Manual Ability Classification System (MACS), Communication Function Classification System (CFCS) as functional classifications, and the physical activity performance of the School Function Assessment (SFA) were measured in 79 children with spastic CP to assess the student's performance of specific school-related functional activities. RESULTS: All the function classification systems were correlated significantly with the physical activity performance of the SFA ($r_s=-.47$ to -.80) (p<.05). The MACS (${\beta}=-.59$), GMFCS (${\beta}=-.23$), CFCS (${\beta}=-.21$), and age (${\beta}=-.15$) in order were predictors of the physical activity performance of the SFA (84.8%)(p<.05). CONCLUSION: These functional classification systems can be used to predict the school-based activity performance in school-aged children with CP. In addition, they can contribute to the selection of areas for intensive interventions to improve the school-based activity performance.

• Journal of Institute of Control, Robotics and Systems
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• v.11 no.12
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• pp.991-995
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• 2005

Sensor networks are the results of convergence of very important technologies such as wireless communication and micro electromechanical systems. In recent years, sensor networks found a wide applicability in various fields such as health, environment and habitat monitoring, military, etc. A very important step for these many applications is pattern classification and recognition of data collected by sensors installed or deployed in different ways. But, pattern classification and recognition are sometimes difficult to perform. Systematic approach to pattern classification based on modern teaming techniques like Multivariate Gaussian mixture models, can greatly simplify the process of developing and implementing real-time classification models. This paper proposes a new recognition system which is hierarchically composed of many sensor nodes haying the capability of simple processing and wireless communication. The proposed system is able to perform classification of sensed data using the Multivariate Gaussian function. In order to verify the usefulness of the proposed system, it was applied to hand gesture recognition system.

• Proceedings of the KSRS Conference
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• 2008.10a
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• pp.169-172
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• 2008

Land-use or land-cover classification of satellite images is one of the important tasks in remote sensing application and many researchers have been tried to enhance classification accuracy. Previous studies show that the classification technique based on wavelet transform is more effective than that of traditional techniques based on original pixel values, especially in complicated imagery. Various wavelets can be used in wavelet transform. Wavelets are used as basis functions in representing other functions, like sinusoidal function in Fourier analysis. In these days, some basis functions such as Haar, Daubechies, Coiflets and Symlets are mainly used in 2D image processing. Selecting adequate wavelet is very important because different results could be obtained according to the type of basis function in classification. However, it is not easy to choose the basis function which is effective to improve classification accuracy. In this study, we computed the wavelet coefficients of satellite image using 10 different basis functions, and then classified test image. After evaluating classification results, we tried to ascertain which basis function is the most effective for image classification. We also tried to see if the optimum basis function is decided by energy parameter before classifying the image using all basis function. The energy parameter of signal is the sum of the squares of wavelet coefficients. The energy parameter is calculated by sub-bands after the wavelet decomposition and the energy parameter of each sub-band can be a favorable feature of texture. The decision of optimum basis function using energy parameter in the wavelet based image classification is expected to be helpful for saving time and improving classification accuracy effectively.

• The Journal of the Korea Contents Association
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• v.10 no.1
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• pp.317-324
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• 2010

The purpose of this study was to examine the validity of the Manual Ability Classification System (MACS) by analysing of relation between MACS and Jebsen-Talyor Hand Function Test. The concurrent validity was examined by calculation of correlation between MACS and Jabsen-Talyor Hand Function test and the discriminant validity was examined by measurement of hand function difference according to MACS level. For this, eighty-one children with spastic cerebral palsy were employed in this study. The children were evaluated by using the MACS and Jebsen-Taylor Hand Function Test for their hand function. There were a significant correlation between the MACS and Hand function (r = .870, p < .05). The good correlation between the MACS and subtest of Jabsen-Talyor Hand function (p < .05). The hand function according to the MACS level were different significantly (p < .05). The MACS is valid classification system for assessment of hand function of children with cerebral palsy. The MACS in practice will provide usefulness for assessment of hand function in children with spastic cerebral palsy.

• Journal of Korean Society of Archives and Records Management
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• v.17 no.2
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• pp.129-163
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• 2017

This study investigated the administrative history, from the introduction of the "Standard of Government Function Classification" (BRM) to its development and application. Through the results of the survey, the causes of the problems observed in the current government's functional classification system were revealed. The current survey examined the functional classification scheme of the central government and local governments on the "cultural heritage" policy area (9 major functions, 59 middle functions, 297 small functions, and 1,287 unit tasks). It confirmed the problem of the separation of functions between central and local governments as well as other problems. Among the problems, this study proposed an improvement model through four representative cases such as the "designation of cultural heritage." In order to reorganize the "Standard of Government Function Classification," it is necessary to design a business function with the reproduction of tasks, establish a system for management and operation in order to maintain the consistency of the business function, educate users, and suggest continuous improvement.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.10 no.1
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• pp.59-64
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• 2010

To improve system performance, we apply the concept of membership function to Variance Considered Machines (VCMs) which is a modified algorithm of Support Vector Machines (SVMs) proposed in our previous studies. Many classification algorithms separate nonlinear data well. However, existing algorithms have ignored the fact that probabilities of error are very high in the data-mixed area. Therefore, we make our algorithm ignore data which has high error probabilities and consider data importantly which has low error probabilities to generate system output according to the probabilities of error. To get membership function, we calculate sigmoid function from the dataset by considering means and variances. After computation, this membership function is applied to the VCMs.

• The Journal of Korean Academy of Sensory Integration
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• v.10 no.1
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• pp.11-20
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• 2012

Objective : The purpose of this study is intended to provide useful information about the disability evaluation indicators, the Modified Barthel Index (MBI) as a measurement tool for assessing the ability to perform activities of daily living through the correlation between the Modified Barthel Index (MBI) and the Manual Ability Classification System (MACS), and Gross Motor Function Classification System (GMFCS). Methods : The subject was 82 children with cerebral palsy. The validity was aexamined by calculation of correlation between the Modified Barthel Index (MBI), the Manual Ability Classification System (MACS) and Gross Motor Function Classification System (GMFCS). Results : There were a good significant correlation between the MBI and MACS (r = -.765, p <0.001), the MBI and the GMFCS (r = -.851, p < 0.001) and the MACS and the GMFCS (r = .615, p <0.001). Conclusion : The close correlation between the MBI that is used as the basis of grading cerebral palsy and high reliability and validity of the MACS, GMFCS suggest that disability evaluation indicators, the MBI could be useful for children with disabilities.

• Korean Journal of Remote Sensing
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• v.24 no.1
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• pp.57-64
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• 2008

In the previous study, the Haar wavelet was used as the sole basis function for the 3D discrete wavelet transform because the number of bands is too small to decompose a remotely sensed image in band direction with other basis functions. However, it is possible to use other basis functions for wavelet decomposition in horizontal and vertical directions because wavelet decomposition is independently performed in each direction. This study aims to classify a high spatial resolution image with the six types of basis function including the Haar function and to compare those results. The other wavelets are more helpful to classify high resolution imagery than the Haar wavelet. In overall accuracy, the Coif4 wavelet has the best result. The improvement of classification accuracy is different depending on the type of class and the type of wavelet. Using the basis functions with long length could be effective for improving accuracy in classification, especially for the classes of small area. This study is expected to be used as fundamental information for selecting optimal basis function according to the data properties in the 3D DWT based image classification.

• ETRI Journal
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• v.28 no.6
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• pp.777-786
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• 2006

Since the introduction of competition in the telecommunication market due to the growth of the interconnection between heterogeneous networks, particularly fixed and mobile networks, the interconnection charge based on traffic-sensitive (TS) and non-traffic-sensitive (NTS) costs has become more important. Although there have been many studies of the public switched telephone network (PSTN), previous studies of TS and NTS costs in mobile networks are very few. In this paper, as a pilot study, we propose three criteria and a procedure for the classification of TS and NTS costs based on mobile systems. The three criteria are the following: function type, investment requirement, and main exhaust driver. Moreover, for a CDMA mobile system, strongly TS, strongly NTS, and mixed components are classified by the proposed criteria and procedure. The proposed criteria, procedure, and classification can provide a systematic and useful guideline to decide the scope of mobile facilities and to determine the terminating cost on mobile networks from fixed networks.