• Journal of Korea Technology Innovation Society
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• v.11 no.4
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• pp.592-612
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• 2008

The convergence of technology as a major breakthrough in technology innovation has been generated and developed. With the advent of the 21st century characterized by the knowledge-based economy, it is happening even more frequently and vigorously than ever. However, study on classification system or definition of notions is necessary as the convergence of technology is still in the early stage. The existing classification system has limited application to the convergence of technology. With no standard available for the classification of the technology convergence, there has been much concern for duplicative R&D investment. On this ground, a new and reformed classification system for the convergence of technology and definition of notions are needed. Previous studies regard base technologies used in the technology convergence and new convergence technologies as important. However, this paper views convergence of technology as a dynamic phenomenon and puts an emphasis on the cause of technology convergence, not on the new technology itself and examines whether base technologies go back to their original state after the completion of technology convergence. This kind of approach will classify technology convergence by characteristics. Although more researches including quantitative analysis are necessary, this paper expects to offer help with further researches on classification system.

• The Journal of the Acoustical Society of Korea
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• v.28 no.1
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• pp.32-43
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• 2009

In this paper, we improve the performance of cardiac disorder classification by continuous heart sound signals using automatic segmentation and extreme learning machine (ELM). The accuracy of the conventional cardiac disorder classification systems degrades because murmurs and click sounds contained in the abnormal heart sound signals cause incorrect or missing starting points of the first (S1) and the second heart pulses (S2) in the automatic segmentation stage, In order to reduce the performance degradation due to segmentation errors, we find the positions of the S1 and S2 pulses, modify them using the time difference of S1 or S2, and extract a single period of heart sound signals. We then obtain a feature vector consisting of the mel-scaled filter bank energy coefficients and the envelope of uniform-sized sub-segments from the single-period heart sound signals. To classify the heart disorders, we use ELM with a single hidden layer. In cardiac disorder classification experiments with 9 cardiac disorder categories, the proposed method shows the classification accuracy of 81.6% and achieves the highest classification accuracy among ELM, multi-layer perceptron (MLP), support vector machine (SVM), and hidden Markov model (HMM).

• Clinics in Shoulder and Elbow
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• v.8 no.1
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• pp.36-42
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• 2005

Purpose: To evaluate the clinical results of anterior subcutaneous ulnar nerve transposition operation and the factors that influence the results for cubital tunnel syndrome. Materials and Methods: Seventeen cases of cubital tunnel syndrome were treated by anterior subcutaneous transposition between March 2001 and December 2003. The mean age was 56 years and mean follow up period was 20.4 months. All patients were reviewed retrospectively. The preoperative evaluation was done by Dellon's classification and the clinical results were evaluated by Messina’s classification. We analyzed the effect of the operation and the relations between the results and the preoperative factors, for example, duration of symptom, age, cause of illness, present of association with diabetes mellitus or preoperative flexion contracture of the elbow were analyzed. Results: The results according to Messina's classification were 4 cases of excellent, 9 cases of good, 3 cases of fair, and 1 case of poor. The preoperative factors like duration of symptom, age, cause of illness and flexion contracture of the elbow didn't show any statistical difference in the result of operation, but the cases which have diabetes mellitus were unsatisfactory with statistical difference (p=0.018). Conclusion: Anterior subcutaneous ulnar nerve transposition is relatively easy and good operative method in cubital tunnel syndrome.

• Journal of the Korean Society of Radiology
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• v.82 no.4
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• pp.791-807
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• 2021

Vasculitis is a systemic disease, characterized by inflammation of the vascular wall. Although rare, it is sometimes life-threatening due to diffuse pulmonary hemorrhage or acute glomerulonephritis. Besides primary vasculitis, whose cause is unknown, numerous conditions such as autoimmune diseases, drugs, infections, and tumors can cause secondary vasculitis. Vasculitis displays various non-specific symptoms, signs, and laboratory findings; hence, diagnosis of the disease requires integration of various results including clinical features, imaging findings, autoantibody tests, and pathological findings. In this review, we have discussed the clinical, radiologic, and pathological features of vasculitis. Further, we elaborated the imaging findings and differential diagnosis of typical vasculitis that frequently involves the lung and introduced a new international classification of vasculitis, the Diagnostic and Classification Criteria in Vasculitis.

• Journal of Integrative Natural Science
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• v.17 no.1
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• pp.1-12
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• 2024

Many abnormal climate events are occurring around the world. The cause of abnormal climate is related to temperature. Factors that affect temperature include excessive emissions of carbon and greenhouse gases from a global perspective, and air circulation from a local perspective. Due to the air circulation, many abnormal climate phenomena such as abnormally high temperature and abnormally low temperature are occurring in certain areas, which can cause very serious human damage. Therefore, the problem of abnormal temperature should not be approached only as a case of climate change, but should be studied as a new category of climate crisis. In this study, we proposed a model for the classification of abnormal temperature using random forests based on various meteorological data such as longitudinal observations, yellow dust, ultraviolet radiation from 2018 to 2022 for each region in Korea. Here, the meteorological data had an imbalance problem, so the imbalance problem was solved by oversampling. As a result, we found that the variables affecting abnormal temperature are different in different regions. In particular, the central and southern regions are influenced by high pressure (Mainland China, Siberian high pressure, and North Pacific high pressure) due to their regional characteristics, so pressure-related variables had a significant impact on the classification of abnormal temperature. This suggests that a regional approach can be taken to predict abnormal temperatures from the surrounding meteorological environment. In addition, in the event of an abnormal temperature, it seems that it is possible to take preventive measures in advance according to regional characteristics.

• Journal of Oriental Neuropsychiatry
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• v.7 no.1
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• pp.137-153
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• 1996

Through the classification of region and kinds of illness about the death of vagrants from 1906 to 1942, the results on the study of vagrants under the rule of Japanese imperialism are followings.1. The statistics about the death of vagrants from 1906 to 1912 have no coherence. So this study excludes that time.2. A mental disease as a cause of death of vagrants is 25.4%. It shows the highest ratio of all the other diseases.3. A mental, nervous disease among the cause of vagrants' death is 15%.4. On outbreak ration of mental disease is 26.7 times in men, 24.6 times in women higher, and on nervous disease 48.1 times in man, 48.9 times in woman higher than Japanese.5. Regional outbreak ratio is higher than Japan. The orders are Chonlabukdo, Chungcheongbukdo, Hwanghaedo, Kangwondo. The above results show that vagrants under the rule of Japanese imperialim is produced by cause of disease. The cause of vagrants' death is also related to social situation at that times. And it accord with the basis of documents. The relation between the death of vagrants and mental, nervous disease are considered to be studied in detailI.

• The Korean Journal of Health Service Management
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• v.13 no.3
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• pp.13-26
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• 2019

Objectives: To investigate whether medical institutions can prevent accidents by analyzing the root cause of a medical accident and identifying the tendencies. Methods: A total of 345 medical cases were used for the RCA(Root Cause Analysis). The root causes were classified using the SHELL model. The suitability of the model was confirmed by SPSS's MDPREF and Euclidean distance. An SPSS20.0 hierarchical regression analysis was used as an influencing factor on the degree of injury resulting from medical accidents. Results: The SHELL model was suitable for classification. The rates of accident causes were LS49%, L34%, LL10.2%, LE3.7%, LH2.3%. The order in which the degree of a patient's injury was affected were: Risk Threshold (${\beta}=.180$), Time (${\beta}=.175$), Surgical stage (${\beta}=-.166$), Do not use procedure (${\beta}=.147$). Conclusions: Health care institutions should remove priorities through system improvement and training. For patients' safety, the five factors of the SHELL model should be managed in harmony.

• Archives of Plastic Surgery
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• v.35 no.4
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• pp.455-460
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• 2008

Purpose: We have classified blepharoptosis into the categories including pseudoptosis in Koreans and compared with other previous studies. Methods: Total of 250 patients(398 eyes) who underwent surgery for blepharoptosis from 1987 to 2006 were studied. By classification of Beard, patients were categorized into congenital, acquired and pseudo blepharoptosis and later they were reclassified by their etiologies. Also addition of pseudoptosis to the classification of Frueh, blepharoptosis were categorized into neurogenic type, myogenic type, aponeurotic type, mechanical type and pseudoptosis. And we divided these cases by the degree of blepharoptosis, levator function and the operation methods. Results: Out of the 250 patients, 175 patients were congenital type, 49 were acquired type and 26 were pseudoptosis. According to the mechanistic classification, 177 myogenic type, 30 aponeurotic, 7 mechanic, 8 neurogenic and 28 pseudoptosis were categorized. Regarding severity of blepharoptosis, there were 29.2% of mild, 40% of moderate, and 30.8% of severe cases. Out of the 398 cases, in terms of the operation methods, there were 39 aponeurosis plication, 184 levator resection, 5 Muller tucking, 60 Orbicularis oculi muscle flap, 66 frontalis transfer, and 21 blepharoplasty. Conclusion: The cause and degree of ptosis, and levator function are very important when considering the amount of resected muscle. There were only a few studies about blepharoptosis classification including pseudoptosis category. Therefore, through this study, we can investigate the relationship between the pseudoptosis and the others. This study could be useful for the making future management plans of blepharoptosis in Korean patients.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.18 no.7
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• pp.1531-1539
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• 2014

Premature ventricular contraction(PVC) is the most common disease among arrhythmia and it may cause serious situations such as ventricular fibrillation and ventricular tachycardia. Nevertheless personalized difference of ECG signal exist, performance degradation occurs because of carrying out diagnosis by general classification rule. In other words, the design of algorithm that exactly detects abnormal signal and classifies PVC by analyzing the persons's physical condition and/or environment and variable QRS pattern is needed. Thus, PVC classification by personalized abnormal signal detection and QRS pattern variability is presented in this paper. For this purpose, we detected R wave through the preprocessing method and subtractive operation method and selected abnormal signal sets. Also, we classified PVC in realtime through QS interval and R wave amplitude. The performance of abnormal beat detection and PVC classification is evaluated by using MIT-BIH arrhythmia database. The achieved scores indicate the average of 98.33% in abnormal beat classification error and 94.46% in PVC classification.

• Journal of the Korea Society of Computer and Information
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• v.27 no.5
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• pp.55-67
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• 2022

Sensor data can provide fault diagnosis for equipment. However, the cause analysis for fault results of equipment is not often provided. In this study, we propose an explainable convolutional neural network framework for the sensor-based time series classification model. We used sensor-based time series dataset, acquired from vehicles equipped with sensors, and the Wafer dataset, acquired from manufacturing process. Moreover, we used Cycle Signal dataset, acquired from real world mechanical equipment, and for Data augmentation methods, scaling and jittering were used to train our deep learning models. In addition, our proposed classification models are convolutional neural network based models, FCN, 1D-CNN, and ResNet, to compare evaluations for each model. Our experimental results show that the ResNet provides promising results in the context of time series classification with accuracy and F1 Score reaching 95%, improved by 3% compared to the previous study. Furthermore, we propose XAI methods, Class Activation Map and Layer Visualization, to interpret the experiment result. XAI methods can visualize the time series interval that shows important factors for sensor data classification.