• Health Policy and Management
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• v.15 no.4
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• pp.46-64
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• 2005

This study was conducted to verify the current criteria and classification system used to determine specialized general hospitals status. In this study, we proposed a new classification system which Is simpler and more convenient than the current one. In the new classification system clinical procedure was chosen as the unit of analysis in order to reflect all the resource consumption and the complexities and degree of medical technologies in determining specialized general hospitals. We developed a statistical model and applied this model to 117 general hospitals which claim their national insurance through electronic data interchange(EDI). Analysis based on 984 clinical procedures and medical facilities' characteristic variable discriminated specialized general hospital in present without misclassification. It means that we can determine specialized general hospital's permission In new way without using the current complicated criteria. This study discriminated specialized general hospital by the new proposed model based on clinical procedures provided by each hospital. For clustering the same types of medical facilities using 984 clinical procedures, we executed multidimensional scale analysis and divided 117 hospitals into 4 groups by two axises : a variety of procedure and the Proportion of high technology Procedure. Therefore, we divided 117 hospitals into 4 groups and one of them was considered as specialized general hospital. In discriminating analysis, we abstracted proportion of 16 clinical procedures which effect on discriminating the specialized general hospital in statistical system also we identify discriminating function which include these variables. As a result, we identify 2 discriminating functions, one is for current discriminating system and the other two is for new discriminating system of specialized general hospital.

• Journal of the Korean Institute of Intelligent Systems
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• v.25 no.5
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• pp.483-488
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• 2015

This paper presents a local binary pattern(LBP) for effectively classifying textures, which is based on the multidimensional intensity difference between the adjacent pixels in the block image. The intensity difference by considering the a extent of 4 directional changes(verticality, horizontality, diagonality, inverse diagonality) in brightness between the adjacent pixels is applied to reduce the computation load as a results of decreasing the levels of histogram for classifying textures of image. And the binary patterns that is represented by the relevant intensities within a block image, is also used to effectively classify the textures by accurately reflecting the local attributes. The proposed method has been applied to classify 24 block images from USC Texture Mosaic #2 of 128*128 pixels gray image. The block images are different in size and texture. The experimental results show that the proposed method has a speedy classification and makes a free size block images classify possible. In particular, the proposed method gives better results than the conventional LBP by increasing the range of histogram level reduction as the block size becomes larger.

• International Journal of Computer Science & Network Security
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• v.23 no.3
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• pp.67-80
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• 2023

Rice is an important food crop for most of the population in Nowadays, psychologists consider social media an important tool to examine mental disorders. Among these disorders, depression is one of the most common yet least cured disease Since abundant of writers having extensive followers express their feelings on social media and depression is significantly increasing, thus, exploring the literary text shared on social media may provide multidimensional features of depressive behaviors: (1) Background: Several studies observed that depressive data contains certain language styles and self-expressing pronouns, but current study provides the evidence that posts appearing with self-expressing pronouns and depressive language styles contain high emotional temperatures. Therefore, the main objective of this study is to examine the literary cyber writers' posts for discovering the symptomatic signs of depression. For this purpose, our research emphases on extracting the data from writers' public social media pages, blogs, and communities; (3) Results: To examine the emotional temperatures and sentences usage between depressive and not depressive groups, we employed the SentiStrength algorithm as a psycholinguistic method, TF-IDF and N-Gram for ranked phrases extraction, and Latent Dirichlet Allocation for topic modelling of the extracted phrases. The results unearth the strong connection between depression and negative emotional temperatures in writer's posts. Moreover, we used Naïve Bayes, Support Vector Machines, Random Forest, and Decision Tree algorithms to validate the classification of depressive and not depressive in terms of sentences, phrases and topics. The results reveal that comparing with others, Support Vectors Machines algorithm validates the classification while attaining highest 79% f-score; (4) Conclusions: Experimental results show that the proposed system outperformed for detection of depression trends in literary cyber writers using sentiment analysis.

• The Journal of the Korea Contents Association
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• v.22 no.5
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• pp.15-25
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• 2022

This study aims to identify the family and lineage of a part of a "Fish Tribe Conference" in the section Tokkijeon by utilizing computer literature analysis techniques. First of all, we encode the classification for a pairwise comparison's type of each paragraph to build a corpus, and based on this, we use the Hamming distance to calculate the distance matrix between each classification for a pairwise comparison's. We visualized classification for a pairwise comparison's clustering pattern by applying multidimensional scale method, and hierarchical clustering to explore the characteristics of the 'fish family' line and lineage compared to the existing cluster analysis study on entire paragraphs of "Tokkijeon". As a result, unlike the cluster analysis of the entire paragraph of "Tokkijeon", which consists of six categories, the "Fish Tribe Conference" section has five categories and some classification for a pairwise comparison's accesses. The results of this study are that the relative distance between Yibon was measured and systematic classification was performed in an objective and empirical way by calculation, and the characteristics of the line of the fish family were revealed compared to the analysis of the entire rabbit exhibition.

• Journal of the Korean Association of Geographic Information Studies
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• v.27 no.1
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• pp.115-127
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• 2024

This research aimed to construct models with various structures based on the Transformer module and to perform land cover classification, thereby examining the applicability of the Transformer module. For the classification of land cover, the Unet model, which has a CNN structure, was selected as the base model, and a total of four deep learning models were constructed by combining both the encoder and decoder parts with the Transformer module. During the training process of the deep learning models, the training was repeated 10 times under the same conditions to evaluate the generalization performance. The evaluation of the classification accuracy of the deep learning models showed that the Model D, which utilized the Transformer module in both the encoder and decoder structures, achieved the highest overall accuracy with an average of approximately 89.4% and a Kappa coefficient average of about 73.2%. In terms of training time, models based on CNN were the most efficient. however, the use of Transformer-based models resulted in an average improvement of 0.5% in classification accuracy based on the Kappa coefficient. It is considered necessary to refine the model by considering various variables such as adjusting hyperparameters and image patch sizes during the integration process with CNN models. A common issue identified in all models during the land cover classification process was the difficulty in detecting small-scale objects. To improve this misclassification phenomenon, it is deemed necessary to explore the use of high-resolution input data and integrate multidimensional data that includes terrain and texture information.

• Investigative Magnetic Resonance Imaging
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• v.2 no.1
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• pp.58-66
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• 1998

Purpose : This paper introduces a new three dimensional magnetic Resonance Image classification which is based on Mar kov Random Field-Gibbs Random Field with a line model. Material and Methods : The performance of the Gibbs Classifier over a statistically heterogeneous image can be improved if the local stationary regions in the image are disassociated from each other through the mechanism of the interaction parameters defined at the local neighborhood level. This usually involves the construction of a line model for the image. In this paper we construct a line model for multisignature images based on the differential of the image which can provide an a priori estimate of the unobservable line field, which may lie in regions with significantly different statistics. the line model estimated from the original image data can in turn be used to alter the values of the interaction parameters of the Gibbs Classifier. Results : MRF-Gibbs classifier for volumetric MR images is developed under the condition that the domain of the image classification is $E^{3}$ space rather thatn the conventional $E^{2}$ space. Compared to context free classification, MRF-Gibbs classifier performed better in homogeneous and along boundaries since contextual information is used during the classification. Conclusion : We construct a line model for multisignature, multidimensional image and derive the interaction parameter for determining the energy function of MRF-Gibbs classifier.

• Health Policy and Management
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• v.4 no.2
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• pp.27-57
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• 1994

The objective of running a long-term care institution is to provide services helpful for maintaining, supporting, and improving elderlies' optimum level of physical, mental, and psychosocial functioning. For the purpose of analyzing the current situations of institutional long term care facilities in Korea, 27 facilities were selected proportionately from each of the cities and provinces, out of the total 152 facilities. About 20% of those who were institutionalized during 25 August through 2 Qctober 1993, the 391 elderlies were chosen on a systematic random basis. The instrument of this study was developed by modifying the tools of CARE, MAI and PCTC. A multivariate approach of discriminant analysis and clustering technique were employed for this study. The Stiudy reveals that there is no clear differentiation of goals and functions among the longterm care institutions in Korea. Staffing patte군 of long-term care facilities shows a shortage of nurses, physical therapists, and dieticians. The linkage between acute care facilities and long-term care is weak, and administration of long-term care faciltiy is carried out by non-professionals. They are responsible for assessing health status before entering the facility, and evaluating elderlies' care. Therefore, it is not surprising to find that most of the facilities have accommodated agede regardless of their real needs and health status. Based upon findings of the analysis, this study has classified long-term care facilities into four types : Type I is to help elderlies maintain independence in daily living activities. Type II facilities have the objective of maintaining and improving the current level of elderlies' function. Type III is to maintain maximum independence of elderlies in activities of daily living. And Type IV is identified for the group of facilities designed to restore or improve functional abilities of elderlies. In conclusion, the following suggestions are made : the need for long-term care should be assessed by multidimensional measurement. Institutional long-term care facilities should be classified and developed in response to type of type of care and service need. Both acute and long-term care facilities should be linked together in order to support the evaluation of service operation and program development.

• Journal of Trauma and Injury
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• v.35 no.1
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• pp.12-18
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• 2022

Purpose: Pedicle screw fixation provides 3-column stabilization, multidimensional control, and a higher rate of interbody fusion. Although computed tomography (CT) is recommended for the postoperative assessment of pedicle screw fixation, its use is limited due to the radiation exposure dose. The purpose of this preliminary retrospective study was to assess the clinical usefulness of low-dose mobile cone-beam CT (CBCT) for the postoperative evaluation of pedicle screw fixation. Methods: The author retrospectively reviewed postoperative mobile CBCT images of 15 patients who underwent posterior pedicle screw fixation for spinal disease from November 2019 to April 2020. Pedicle screw placement was assessed for breaches of the bony structures. The breaches were graded based on the Heary classification. Results: The patients included 11 men and four women, and their mean age was 66±12 years. Of the 122 pedicle screws, 34 (27.9%) were inserted in the thoracic segment (from T7 to T12), 82 (67.2%) in the lumbar segment (from L1 to L5), and six (4.9%) in the first sacral segment. Although there were metal-related artifacts, the image of the screw position (according to Heary classification) after surgery could be assessed using mobile CBCT at all levels (T7-S1). Conclusions: Mobile CBCT was accurate in determining the location and integrity of the pedicle screw and identifying the surrounding bony structures. In the postoperative setting, mobile CBCT can be used as a primary modality for assessing the accuracy of pedicle screw fixation and detecting postoperative complications.

• The Journal of the Korean life insurance medical association
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• v.27 no.1
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• pp.33-36
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• 2008

BACKGROUND : The medical claims review(MCR) is unique methodology of medical consultation in terms of insurance claim administration in Korean insurance market. The most important practical matter in the MCR is formatted question. In Korea, medical specialty is composed of 26 legally defined hospital departments. It is worth of studying to investigate type of MCR by hospital departments. METHODS : Fifty Cases of the MCR were selected randomly by statistical program SPSS among 1,032 cases which were performed between April 1, 2006 and March 31 2007. All of selected cases were evaluated one insurance doctor and made a score points from 0 to 10 in terms of hospital department. RESULTS : Multidimensional scaling was performed. The MCR types - diagnosis, malignancy and cause of death are located in the same 2-dimensional configuration area. It can be called as verification of benefit. Others are advice. - such as causality, interpretation, translation, independent medical examination, and so on. DISCUSSION : We can conclude the classification of MCR typology are two main subjects, verification and advice. Theses results are same as previous article which was based on experience.

• Physical Therapy Korea
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• v.23 no.4
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• pp.63-70
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• 2016

Background: The Pediatric Balance Scale (PBS) and the Fullerton Advanced Balance (FAB) scale were used to assess balance function in patients with balance problem. These multidimensional clinical balance scales provide information about potential risk factors for falls. Objects: The purpose of this study was to investigate and compare the predictive properties of the PBS and FAB scales relative to fall risk in children with cerebral palsy (CP) using a receiver operating characteristic analysis. Methods: In total, 49 children with CP (boy=21, girl=28) who were diagnosed with level 1 or 2 according to the Gross Motor Function Classification System participated in this study. The PBS and FAB were performed, and verified cut-off score, sensitivity, specificity, and the area of under the curve (AUC). Results: In this study, the PBS scale was as a predictive measure of fall risk, but the FAB was not significant in children with CP. A cut-off score of 45.5 points provided optimal sensitivity of .90 and specificity of .69 on the PBS, and a cut-off score of 21.5 points provided optimal sensitivity of .90 and specificity of .62 on the FAB. Both scales showed moderately accurate of AUC with .79 and .76, respectively. Conclusion: The PBS is a useful screening tool for predicting fall risk in children with cerebral palsy, and those who score 45.5 or lower indicate a high risk for falls and are in need of balance intervention.