• Proceedings of the Korea Inteligent Information System Society Conference
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• 2001.01a
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• pp.464-469
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• 2001

CRM(Customer Relationship Management : CRM) is an advanced marketing supporting system which analyze customers\` transaction data and classify or target customer groups to effectively increase market share and profit. Many engines were developed to implements the function and those for classification and clustering are considered core ones. In this study, an improved clustering method based on SOM(Self-Organizing Maps : SOM) is proposed. The proposed clustering method finds the optimal number of clusters so that the effectiveness of clustering is increased. It considers all the data types existing in CRM data warehouses. In particular, and adaptive algorithm where the concepts of degeneration and fusion are applied to find optimal number of clusters. The feasibility and efficiency of the proposed method are demonstrated through simulation with simplified data of customers.

• Journal of the Korea Society of Computer and Information
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• v.13 no.6
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• pp.51-58
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• 2008

A version control system is used in a rapidly changed environment or a program which developed in a complicated environment. it is a problem of configuration thread in supporting information that we, in this method, can't know a exactly well-defined configuration rule information and a predefined information. In this paper. Library system is suggested, modelled, and implemented so as to configuration thread control the components required by the user in many ways. As for the library used in the configuration thread control suggested in this paper, the components can be retrieved from the library regardless of the infrastructure, applying the extended facet classification. This retrieval framework is managed using TreeSearch class and the configuration thread control function. The library system of this paper can be used by the interface with other languages, and this system is to have a advantage to extend a facet by user.

• Journal of the Korean Society of School Health
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• v.2 no.1
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• pp.131-146
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• 1989

This study was conducted for the development of recording system of students' health problems, and for the application of International Classification of Health Problem in Primary Care(ICHPPC) as a tool of morbidity classification in school health care. The data were collected from 12th of September to 24th of September in 1988. The objects were composed of health problems written by 10 school nurses who take service in the elementary school. The results were as follows: 1. The features of students' health problmes. The health problems of students were 68 problems from the total numbers of 361 codes of ICHPPC. The 93.4% of health problems was contained in 20 descriptive diagnoses and 97.0% was contained in 30 descriptive diagnoses. According to frequency of main health problems, There were abrasion, scratch and blister(26.7%); disorder of stomach function, other disease of stomach and duodenum (20.4%); headache(10.6%); bruise and contusion (5.3%); acute URI (5.0%); laceration and open wound(4.6%); Insect bite and sting(4.0%); epistaxis(3.4%): abdominal pain(2.6%): superficial tissue(1.7%). Out of all health problems, Category 17(accident, injury and poisoning was 44.7%. and Category 9(digestive system Disease) was 22.2%. 2. Applicability of ICHPPC by the school nurses. School nurses used 68 codes, among the total number of 361 codes from ICHPPC. According to ICHPPC method, school nurses can classified more diverse health problems systematically and objectively than that in other studies on school nurses activities. ICHPPC was found as a useful and applicable tool of morbidity classification in the practice of school nurses.

• Journal of the Korean Society for Library and Information Science
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• v.7
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• pp.3-67
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• 1980

Because of the changes made in the modes of cataloguing and classification in its long history, the present catalogue of the National Central Library has become complicated and provides an inadequate guide to its collection. There can be no doubt that this is a serious deficiency in a closed access library since materials housed in the library are virtually inaccessible to unskilled readers. The whole breakdown of the efficiency of the catalogue is emminent and will ultimately create the most serious problems for the library. The main purpose of this survey is: (a) to identify problem areas created by the frequent changes in the cataloguing and classifying principles in the library and (b) to grope a rational direction for the future development. Analysing the various classification schemes and cataloguing rules adopted in processing materials (mainly books) in the library, the following conclusions have been made. A. The library adopted five different clasification schemes in different periods, of which KDCP was used for the most part of its collection. KDCP is recommended to use for the future colletion. A classification development office is recommended to be established within the library, of which the main function is to revise the KDCP in collaboration with the appropriate committee of the Korean Library Association. B. The present practice in the library is to apply three different cataloguing rules and two different author notation tables to the Oriental, classical, and Western collections. Efforts should be made to find out an efficient system so that this variety is simplified. An alphabetical index should be added to the classified catalogue, and improvements are required in the Japanese collection. C. The technical services division is inadequately staffed. The staff should be sufficiently numerous and specially qualified. D. The present financial support for the technical services of the library is inadequate. Sufficient financial provision should be made to ensure the effective work. E. A feasibility study should be carried out to develop a computer processing system for providing machine-readable catalogue records on magnetic tape for use by the library community in Korea.

• Journal of IKEEE
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• v.20 no.4
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• pp.398-411
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• 2016

SVM, a machine learning method, is widely used in image processing for it's excellent generalization performance. However, to add other data to the pre-trained data of the system, we need to train the entire system again. This procedure takes a lot of time, especially in embedded environment, and results in low performance of SVM. In this paper, we implemented an SVM trainer and classifier in an FPGA to solve this problem. We parlallelized the repeated operations inside SVM and modified the exponential operations of the kernel function to perform fixed point modelling. We implemented the proposed hardware on Xilinx ZC 706 evaluation board and used TSR algorithm to verify the FPGA result. It takes about 5 seconds for the proposed hardware to train 2,000 data samples and 16.54ms for classification for $1360{\times}800$ resolution in 100MHz frequency, respectively.

• Journal of Korea Multimedia Society
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• v.22 no.10
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• pp.1168-1177
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• 2019

In order to diagnose and prevent Alzheimer's Disease (AD), it is becoming increasingly important to develop a CAD(Computer-aided Diagnosis) system for AD diagnosis, which provides effective treatment for patients by analyzing 3D MRI images. It is essential to apply powerful deep learning algorithms in order to automatically classify stages of Alzheimer's Disease and to develop a Alzheimer's Disease support diagnosis system that has the function of detecting hippocampus and CSF(Cerebrospinal fluid) which are important biomarkers in diagnosis of Alzheimer's Disease. In this paper, for AD diagnosis, we classify a given MRI data into three categories of AD, mild cognitive impairment, and normal control according by applying 3D brain MRI image to the Faster R-CNN model and detect hippocampus and CSF in MRI image. To do this, we use the 2D MRI slice images extracted from the 3D MRI data of the Faster R-CNN, and perform the widely used majority voting algorithm on the resulting bounding box labels for classification. To verify the proposed method, we used the public ADNI data set, which is the standard brain MRI database. Experimental results show that the proposed method achieves impressive classification performance compared with other state-of-the-art methods.

• Journal of Korean Society of Rural Planning
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• v.29 no.4
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• pp.13-26
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• 2023

Recently, South Korea has prepared laws and systems to systematically manage rural spaces in response to the era of population decline and is making various efforts to promote related policies. However, various basic studies that can support this are still insufficient. In particular, in this study, the functions and roles of each settlement class were established along with the classification of the sedentary classes in rural areas, and the classification system for rural living services was established, and the hierarchy by functional facilities and the minimum standards for vulnerable areas (accessibility) were established. Specifically, in this study, the settlement class was divided into 4 classes of "central area - midpoint area - small point area - hinterland", and each function and role was presented, and the rural living service classification system was finally reestablished as 10 sectors and 31 functional facilities. In addition, the hierarchy and accessibility standards of rural living service functional facilities was set within 5 to 15 minutes for 'lower and basic services', within 10 to 20 minutes for 'medium and basic services', within 15 to 30 minutes for 'intermediate and complex services', within 20 to 60 minutes for 'high car/complex service' and within 10 minutes for 'urgent service'.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.9 no.2
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• pp.322-329
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• 2005

This paper describes a computer vision system based on active IR illumination for real-time gaze discrimination system. Unlike most of the existing gaze discrimination techniques, which often require assuming a static head to work well and require a cumbersome calibration process for each person, our gaze discrimination system can perform robust and accurate gaze estimation without calibration and under rather significant head movement. This is made possible by a new gaze calibration procedure that identifies the mapping from pupil parameters to screen coordinates using generalized regression neural networks (GRNNS). With GRNNS, the mapping does not have to be an analytical function and head movement is explicitly accounted for by the gaze mapping function. furthermore, the mapping function can generalize to other individuals not used in the training. To further improve the gaze estimation accuracy, we employ a reclassification scheme that deals with the classes that tend to be misclassified. This leads to a 10$\%$ improvement in classification error. The angular gaze accuracy is about $5^{circ}$horizontally and $8^{circ}$vertically. The effectiveness of our gaze tracker is demonstrated by experiments that involve gaze-contingent interactive graphic display.

• The Journal of Korean Physical Therapy
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• v.31 no.5
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• pp.279-285
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• 2019

Purpose: This study examined the effects of spinal stabilization exercises using visual feedback on the gross motor function and balance of the sitting posture in children with cerebral palsy. Methods: The subjects were 18 children with cerebral palsy aged 8-15 years in the I-III stages of the Gross Motor Function Classification System. The subjects were divided into an experimental group (n=9) and control group (n=9). The experimental group was treated with 30 minutes of neurodevelopmental treatment and 20 minutes of spinal stabilization exercises using visual feedback. The control group was treated with 30 minutes of neurodevelopmental treatment and 20 minutes of spinal stabilization exercises without visual feedback. Both groups participated in the experiment twice a week for eight weeks. The Gross Motor Function Measurement was performed to evaluate the changes between pre- and the post-intervention in gross motor function. The Seated Limit of Stability Surface Area was measured to evaluate the changes in trunk balance. Results: Both experimental and control groups showed a significant increase in the gross motor function and trunk balance (p<0.05). The experimental group showed a significant increase in gross motor function compared to the control group (p<0.05). The experimental group showed a significant increase in the dynamic trunk balance in all directions when measuring the Seated Limit of Stability Surface Area (p<0.05). Conclusion: Spinal stabilization exercises using visual feedback for the neurodevelopmental treatment of children with cerebral palsy can improve their gross motor function and trunk balance when in a sitting posture more effectively.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.64 no.6
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• pp.922-934
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• 2015

In this paper, The classification between precipitation echo(PRE) and non-precipitation echo(N-PRE) (including ground echo and clear echo) is carried out from weather radar data using neuro-fuzzy algorithm. In order to classify between PRE and N-PRE, Input variables are built up through characteristic analysis of radar data. First, the event classifier as the first classification step is designed to classify precipitation event and non-precipitation event using input variables of RBFNNs such as DZ, DZ of Frequency(DZ_FR), SDZ, SDZ of Frequency(SDZ_FR), VGZ, VGZ of Frequency(VGZ_FR). After the event classification, in the precipitation event including non-precipitation echo, the non-precipitation echo is completely removed by the echo classifier of the second classifier step that is built as Type-2 FCM based RBFNNs. Also, parameters of classification system are acquired for effective performance using PSO(Particle Swarm Optimization). The performance results of the proposed echo classifier are compared with CZ. In the sequel, the proposed model architectures which use event classifier as well as the echo classifier of Interval Type-2 FCM based RBFNN show the superiority of output performance when compared with the conventional echo classifier based on RBFNN.