• Journal of the Korean Society for Library and Information Science
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• v.22
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• pp.259-304
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• 1992

This paper examines 'Religion Class' in the scheme of the DDC. The major findings of the study are summerized as follows. 1. The first edition of DDC was published in 1876 in order to classify Amherst College Library collections. In spite of the continuous study and revision of the experts, the frameworks of the DDC systems are still kept unchanged. Only their subdivisions, reflecting those developments in the academic world, are developed and detailed more sophisticatedly. 2. The division of 200 does not function as generalities for all class of religion. Therefore, it is necessary to amend the division of 200 to serve generalities for all the religions of the world. 3. Standard subdivision for the christian religion and for the non-christian religion is different. So, the mnemonic nature has become weakened due to the dual standard subdivisions and the classification number becomes much longer and complicated. Therefore, one standard subdivision for all religions of the world is required. 4. Religion science was organized in late 19 C and developed continuously, but the DDC does not accomodate the religion science as a science. Accodingly, the DDC should be revised recognize religion science as a science not the christian science. 5. The deployment of classification scheme in Dewey's 200 is severely biased. That is to say, 9 division were assigned for christian religion, whereas only 1 division was assigned for non-christian religion. Therefore, an adjustment should be made to allocate subdivisions equally to all religions of the world. 6. General classification order of religion is prehistoric, primitive, ancient, modem and world religion in religion science. But, DDC does not accept this general classification order of religion, sticking to the biased expansion towards christianity. Therefore, DDC must adopt the general classification order of religion in the religion science. 7. Lastly, because of the limitation of decimal notation in DC, DDC does not accomodate new subject equally and classification number becomes longer. Therefore, centesimal expansion is proposed in order to make the classification number short, to enlarge its capacity of inclusion of new subject and to maintain consistency in the scheme.

• Journal of the Korean Data and Information Science Society
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• v.27 no.4
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• pp.947-957
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• 2016

KCI is a database for the citations of journals and papers published in Korea. Classification of a journal listed in KCI was mainly determined by the publisher who registered the journal at the time of application for the journal. However, journal classification in KCI was known for not properly representing the quoting rate between journals. In this study, we extracted communities of the journals registerd in KCI based on quoting relationship using various network clustering algorithms. Among them, the infomap algorithm turned out to give a classification more being alike to the current KCI's in the aspect of the modular structure.

• International Journal of Computer Science & Network Security
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• v.22 no.10
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• pp.246-256
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• 2022

Recently, parents and teachers consider physical education as a minor subject for students in elementary and secondary schools. Physical education performance has become increasingly significant as parents and schools pay more attention to physical schooling. The sports mining with distribution analysis model considers different factors, including the games, comments, conversations, and connection made on numerous sports interests. Using different machine learning/deep learning approach, children's athletic and academic interests can be tracked over the course of their academic lives. There have been a number of studies that have focused on predicting the success of students in higher education. Sports interest prediction research at the secondary level is uncommon, but the secondary level is often used as a benchmark to describe students' educational development at higher levels. An Automated Student Interest Prediction on Sports Mining using DL Based Bi-directional Long Short-Term Memory model (BiLSTM) is presented in this article. Pre-processing of data, interest classification, and parameter tweaking are all the essential operations of the proposed model. Initially, data augmentation is used to expand the dataset's size. Secondly, a BiLSTM model is used to predict and classify user interests. Adagrad optimizer is employed for hyperparameter optimization. In order to test the model's performance, a dataset is used and the results are analysed using precision, recall, accuracy and F-measure. The proposed model achieved 95% accuracy on 400^th instances, where the existing techniques achieved 93.20% accuracy for the same. The proposed model achieved 95% of accuracy and precision for 60%-40% data, where the existing models achieved 93% for accuracy and precision.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.7
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• pp.2667-2682
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• 2015

Due to the wide application of face recognition (FR) in information security, surveillance, access control and others, it has received significantly increased attention from both the academic and industrial communities during the past several decades. However, partial face occlusion is one of the most challenging problems in face recognition issue. In this paper, a novel method based on linear regression-based classification (LRC) algorithm is proposed to address this problem. After all images are downsampled and divided into several blocks, we exploit the evaluator of each block to determine the clear blocks of the test face image by using linear regression technique. Then, the remained uncontaminated blocks are utilized to partial occluded face recognition issue. Furthermore, an improved Distance-based Evidence Fusion approach is proposed to decide in favor of the class with average value of corresponding minimum distance. Since this occlusion removing process uses a simple linear regression approach, the completely computational cost approximately equals to LRC and much lower than sparse representation-based classification (SRC) and extended-SRC (eSRC). Based on the experimental results on both AR face database and extended Yale B face database, it demonstrates the effectiveness of the proposed method on issue of partial occluded face recognition and the performance is satisfactory. Through the comparison with the conventional methods (eigenface+NN, fisherfaces+NN) and the state-of-the-art methods (LRC, SRC and eSRC), the proposed method shows better performance and robustness.

• Journal of Multimedia Information System
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• v.6 no.4
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• pp.225-234
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• 2019

Deep learning has become increasingly popular in both academic and industrial areas nowadays. Various domains including pattern recognition, Computer vision have witnessed the great power of deep neural networks. However, current studies on deep learning mainly focus on quality data sets with balanced class labels, while training on bad and imbalanced data set have been providing great challenges for classification tasks. We propose in this paper a method of data analysis-based data reduction techniques for selecting good and diversity data samples from a large dataset for a deep learning model. Furthermore, data sampling techniques could be applied to decrease the large size of raw data by retrieving its useful knowledge as representatives. Therefore, instead of dealing with large size of raw data, we can use some data reduction techniques to sample data without losing important information. We group PCB characters in classes and train deep learning on the ResNet56 v2 and SENet model in order to improve the classification performance of optical character recognition (OCR) character classifier.

• Child Health Nursing Research
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• v.6 no.2
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• pp.119-131
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• 2000

The purpose of this study was to identify the trends and contents of intervention towards children using meta analysis, to support the basis for using in the field and research method about nursing intervention. We used 27 materials which was reported from 1970 to August, 1999 : dissertation study and Korean Nurses' Academic society Journals, the Journal of Korean Academic society of Adult Nursing, The Korea Journal of Maternal and Child Health Nursing. The types of intervention we used came from 3 different researchers. Snyder showed cognitive, movement, social sensory intervention. McCloskey & Bulechek categorized as the following : self-care assistance, acute care management, life-style alteration, health promotion, life support intervention, Craft & Denehy classified psychosocial intervention and biophysiological intervention. Some findings are summarized as follow : Out of the 27 researches sensory intervention had the most in there thesis, recently cognitive intervention research has a tendency to increase. 18 researches has acute care management in there theses, and health promotion was found the least. Out of the 27 thesis 15 thesis was classified as biophysiological intervention and 12 had psychosocial. 27 thesis had 11 types of interventions which originally was categorized by Snyder, therefore sensory intervention thesis had the most. 11 types of intervention which originally was classified by McClosky & Bulechek, teaching and information had the most out of acute care management. Out of 27 thesis, 14 had dealt with newborns, especially newborns with sensory intervention. Therefore school age and above had cognitive intervention which was used for teaching and information. Infants, preschool, schoolage children received acute care management the most, health promotion intervention was used towards adolescences. Depending on the characteristics of dependent variables, it was analysed using meta however 17 thesis are possible except primary experimental research. Mean effect size comparison by Snyder classification, cognitive intervention was the largest mean(1.51), sensory intervention was larger(0.71) also, movement intervention was in the middle(0.56) as shown. Comparison done by McClosky & Bulechek, the intervention leading to life style alteration was the largest mean(1.97), teaching was used the most. Comparison by Craft & Denehy classification, psychosocial intervention was larger(1.15) than biophysiological intervention (0.67). The result of nursing intervention through age classification, the largest weighted mean effect size in the research was towards infants and neonates. The research which was focused on nursing intervention, has important meaning in nursing practice and knowledge development. When we know that children's nursing intervention is necessary and overcome our biased view, efficiency of children's nursing intervention are increased and professionalized. Therefore results will be important basic data to guide a development of child nursing intervention & classification.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.9
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• pp.345-351
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• 2020

Administrative agencies today are paying keen attention to big data analysis to improve their policy responsiveness. Of all the big data, news articles can be used to understand public opinion regarding policy and policy issues. The amount of news output has increased rapidly because of the emergence of new online media outlets, which calls for the use of automated bots or automatic document classification tools. There are, however, limits to the automatic collection of news articles related to specific agencies or departments based on the existing news article categories and keyword search queries. Thus, this paper proposes a method to process articles using classification glossaries that take into account each agency's different work features. To this end, classification glossaries were developed by extracting the work features of different departments using Word2Vec and topic modeling techniques from news articles related to different agencies. As a result, the automatic classification of newspaper articles for each department yielded approximately 71% accuracy. This study is meaningful in making academic and practical contributions because it presents a method of extracting the work features for each department, and it is an unsupervised learning-based automatic classification method for automatically classifying news articles relevant to each agency.

• The Academic Congress of Korean Shoulder and Elbow Society
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• 2009.03a
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• pp.128-129
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• 2009

This study suggests isolated Type IV-MO or Type IV-LO fractures could be treated with nonsurgical treatment because they do not interfere with normal elbow kinematics. Valgus and external rotation instability were influenced by total articular surface, however, posterior and proximal translation were influenced by isolated articular surface involvement of coronoid. Further clinical studies are warranted to validate these in vitro findings.

• The Korean Journal of Nuclear Medicine Technology
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• v.26 no.2
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• pp.37-42
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• 2022

Purpose Since 1985, the Korean society of nuclear medicine technology (KSNMT) has been engaged in academic activities related to nuclear medicine imaging. From 2017 to 2021, the papers published in the journal were classified by the specific fields to examine the trends in the research and the direction of nuclear medicine in comparison with the papers submitted to the Korean Society of Nuclear Medicine (KSNM) during the same period. Materials and Methods From 2017 to 2021, papers submitted to KSNMT and KSNM were classified and databaseization using the Excel program by submission type, examination equipment, and examination field. Through this data, the number of papers published in journals by year, the number of papers submitted by detailed fields, and key words by era were analyzed and compared. Results The papers included by journal was 57 KSNMT and 280 KSNM. The major large classification of equipment, PET, Planar and SPECT was 26.3%, 21.1%, 19.3% in the KSNMT, KSNM was 49.6%, 6.4%, and 9.3%, with 66.7% and 65.3%, respectively. the major medium classification of equipment, industrial safety, urogenital system, nervous system, and quality control accounted for 54.4% of the total papers of the total ratio in the KSNMT, while the medium classification of oncology, endocrine system, urogenital system, therapy, and nervous system accounted for 61.1% of KSNM. In the major small classification of image acquisition, improvement effect, and exposure management accounted for 70.2% in KSNMT, while the items of image acquisition, report, and improvement effect accounted for 60.7% in KSNM. The major keywords except for equipment-related keywords such as PET/CT, PET/MR, and SPECT were SUV, Planar Image, and Respiration Gating Method in KSNMT and Ga68, Thyroid, and Lymphoma in the KSNM. Conclusion When checking the last 5 years of submissions, we can see that KSNMT is mainly concerned with image acquisition using existing radiotracers, while KSNM has focused on new radiotracers such as ⁶⁸Ga, ¹⁷⁷Lu, etc., and new medical technologies of theranostic. It has been confirmed that more PET-related papers than other examination equipment will account for a greater number of papers, and it is believed that future submissions will also account for a higher proportion of PET-related papers than other equipment.

• Journal of Physiology & Pathology in Korean Medicine
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• v.31 no.4
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• pp.201-212
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• 2017

This study draws pattern differentiations of headache disorders on the ground of modern clinical applications and Korean medical literature. Categorization and symptoms of headache disorders are based on International Classification of Headache Disorders 3rd edition(beta version). And clinical papers are searched in China Academic Journals(CAJ) of China National Knowledge Infrastructure(CNKI). In the aspect of eight principle pattern identification, primary headache occurs due to lots of yang qi and has more inner pattern rather than exterior pattern, heat pattern rather than cold pattern, excess pattern rather than deficiency pattern. And primary headache is related with liver in the aspect of visceral pattern identification and blood stasis, wind and phlegm are relevant mechanisms. Migraine without aura is associated with ascendant hyperactivity of liver yang, phlegm turbidity, sunken spleen qi, wind-heat, blood deficiency or yin deficiency. Migraine with aura is mainly related with wind and it's major mechanisms are ascendant hyperactivity of liver yang, liver fire, yin deficiency of liver and kidney, blood deficiency or liver depression and qi stagnation. High repetition rate of tension-type headache can be identified as heat pattern or excess pattern. And trigeminal autonomic cephalalgias can also be accepted as heat pattern or excess pattern when the occurrence frequency is high and is relevant to combined pattern with excess pattern of external contraction and deficiency pattern of internal damage based on facial symptoms by external contraction and nervous and anxious status by liver deficiency. This study can be expected to be Korean medical basis of clinical practice guidelines on headache by proposing pattern identifications corresponding to the western classifications of headache disorders.