• The Journal of Korean Physical Therapy
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• v.15 no.3
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• pp.126-152
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• 2003

The purpose of this study was to evaluate the value of passive caudal gliding mobilization of the glenohumeral joint on the range of motion (ROM) of active and passive abduction; to evaluate the value of pain relief through visual analogue scale (VAS); to evaluate the correlation between improvement of shoulder abduction and intra-articular movement measured by fluoroscopy in frozen shoulder patients. The subjects consisted of twenty-one patients with clinically diagnosed frozen shoulder (11 males, 10 females) between 40 and 63 years of age (mean age : 52.7 years). The traction and caudal gliding mobilization based on the convex-concave rule in the resting position and at end range of abduction was peformed for 15 minutes per day and was repeated 10 times during a 2 week period. The ROM of abduction was measured by goniometer and pain was measured by VAS. The intra-articular movement was measured by fluoroscope, Neurostar Plus TOP (Siemens, Germany). ROM measurements of each patient was acquired at pre-treatment, immediate post-treatment and 2 week post-treatment. Statistical analysis was performed using SPSS 10.0 for Windows software and data was analyzed using the paired-test and the pearson correlation. The results of this study are as follows: 1. There was a significant decrease of VAS between pre-treatment data and 2 week post-treatment data (P<.05) but no significant difference between pre-treatment and immediate post-treatment data (P>.05). 2. There was a significant increase in ROM of active and passive abduction in the pre-treatment data, immediate post-treatment data, and in 2 week post-treatment data (P<.05). 3. With regard to results of the joint play test, there was a significant difference in the grade of traction between pre-treatment data and immediate post-treatment data and between pre-treatment data and 2 week post-treatment data (P<.05). There was no significant difference between immediate post-treatment data and 2 week post-treatment data (P>.05). 4. With regard to results of the joint play test, there was a significant difference in the grade of caudal gliding between pre-treatment data and immediate post-treatment data and between pre-treatment data and 2 week post-treatment data (P<.05). There was no significant difference between immediate post-treatment data and 2 week post-treatment data (P>.05), 5. With regard to the results of fluoroscopic findings, there was a significant change of the glenohumeral joint space between pre-treatment data and immediate post-treatment data and between immediate post-treatment data and 2 week post-treatment data (P<.05). There was no significant change of the glenohumeral joint space between immediate post-treatment data and 2 week post-treatment data (P>.05). 6. With regard to the results of fluoroscopic findings, there was a significant change of acromiohumeral joint space between the three data (pre-treatment data, immediate post-treatment data, 2 week post-treatment data) (P<.05). 7. Mobility grade by joint play test was significantly increased and was correlated to improved ROM of active and passive abduction (P<.05). In this study of frozen shoulder, passive caudal gliding techniques of the glenohumeral joint results in statistically significant changes in active and passive abduction as well as in VAS. There is also a significant correlation between joint play test and ROM of abduction.

• Restorative Dentistry and Endodontics
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• v.23 no.1
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• pp.110-140
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• 1998

One of the problems facing in all modern dental hospitals is the much efforts, manpower and space are needed to effectively sort and stack patients' charts of the various dental departments. In addition, the storage and prompt arrangement of x-ray films is also a problem. Therefore, if dental charts as well as films could be computerized, it would be easier to store and keep them; by data basing, many space, manpower and cost would be saved: data could also be effectively managed for the purpose of academic researches. This would be an epoch -making event in the development of dental hospital management. The purpose of this study is to develop a dental information processing program, that will be used to store dental treatment records and digital image data using a new record media, the optical card. The patients' charts from the dental hospital were selected. The treatment records of the chart were put into the treatment data -recording area of the program, and the digital images of various dental x-ray films were made with a scanner. These data were stored in the optical card and analyzed to get the following results: 1. In this program it is possible to put treatment records and image data into and out from the optical card, and it is impossible to correct and delete all data recorded on the optical card. 2. All data in the optical card system can be searched and analyzed on database. 3. The resolution of image data stored in optical card is above 5.9 lp/mm. 4, All data of dental charts used as samples, stored to optical cards, occupies average 14%, In conclusion, with the development of the storage system using the optical card, a dental patient's life-time treatment record can be stored in one optical card and used as a substitute for the dental chart.

• KIPS Transactions on Software and Data Engineering
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• v.6 no.6
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• pp.303-308
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• 2017

Nowadays, living standard is improved and people have high interest to the personal health care problem. Accordingly, people desire to know the personal physical condition and the related medical treatment. Thus, there is the necessary of the personalized medical treatment, and there are many studies about the automatic disease diagnosis and the related services. Those studies focus on the particular disease prediction which is based on the related particular data. However, there is no studies about the medical treatment prediction. In our study, national health data based medical treatment predictor is built by using SVM, and the performance is evaluated by comparing with other prediction methods. The experimental results show that the health data based medical treatment prediction resulted in the average accuracy of 80%, and the SVM performs better than other prediction algorithms.

• Journal of Environmental Science International
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• v.31 no.7
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• pp.555-567
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• 2022

With the introduction of the tele-monitoring system (TMS) in South Korea, monitoring of the concentration of pollutants discharged from nationwide water quality TMS attachments is possible. In addition, the Ministry of Environment is implementing a smart sewage system program that combines ICT technology with wastewater treatment plants. Thus, many institutions are adopting the automatic operation technique which uses process operation factors and TMS data of sewage treatment plants. As a part of the preliminary study, a multilayer perceptron (MLP) analysis method was applied to TMS data to identify predictability degree. TMS data were designated as independent variables, and each pollutant was considered as an independent variables. To verify the validity of the prediction, root mean square error analysis was conducted. TMS data from two public sewage treatment plants in Chungnam were used. The values of RMSE in SS, T-N, and COD predictions (excluding T-P) in treatment plant A showed an error range of 10%, and in the case of treatment plant B, all items showed an error exceeding 20%. If the total amount of data used MLP analysis increases, the predictability of MLP analysis is expected to increase further.

• KEPCO Journal on Electric Power and Energy
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• v.7 no.1
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• pp.73-77
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• 2021

As the big data analysis technologies has been developed worldwide, the importance of asset management for electric power facilities based data analysis is increasing. It is essential to secure quality of data that will determine the performance of the RISK evaluation algorithm for asset management. To improve reliability of asset management, asset data must be preprocessed. In particular, the process of cleaning dirty data is required, and it is also urgent to develop an algorithm to reduce time and improve accuracy for data treatment. In this paper, the result of the development of an automatic cleaning algorithm specialized in overhead transmission asset data is presented. A data cleaning algorithm was developed to enable data clean by analyzing quality and overall pattern of raw data.

• Journal of Convergence for Information Technology
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• v.9 no.9
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• pp.195-200
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• 2019

The purpose of this study is to analyze the characteristics of National Health Insurance claim data and to construct a pilot medical episode data considering it. In this study, the trends of respiratory disease (ICD10: J00-J99) cardiovascular disease (ICD10: I00-I99) from the day of onset of treatment to re-admission after admission were confirmed in Seoul, and the largest decrease was observed when the no-treatment period was 0 day. The data reduction rate when the no-treatment period is 0 day is judged to be due to the monthly separation claim of the health insurance claim data. Also, the result that there is a tendency of monthly separation request according to the type of medical treatment. Through this study, we constructed epidemic data for the pilot medical treatment considering the characteristics of the claim data of health insurance, and based on this, it can be used as a data processing method for calculating basic epidemiological information.

• KEPCO Journal on Electric Power and Energy
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• v.7 no.1
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• pp.79-84
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• 2021

The fundamental element to be kept for big data analysis, artificial intelligence technologies and asset management system is a data quality, which could directly affect the entire system reliability. For this reason, the momentum of data cleaning works is recently increased and data cleaning methods have been investigating around the world. In the field of electric power, however, asset data cleaning methods have not been fully determined therefore, automatic cleaning algorithm of asset data for transmission cables has been studied in this paper. Cleaning algorithm is composed of missing data treatment and outlier data one. Rule-based and expert opinion based cleaning methods are converged and utilized for these dirty data.

• Korean Journal of Artificial Intelligence
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• v.10 no.2
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• pp.13-18
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• 2022

The role of artificial medical intelligence through medical big data has been focused on data-based medical device business and medical service technology development in the field of diagnostic examination of the patient's current condition, clinical decision support, and patient monitoring and management. Recently, with the 4th Industrial Revolution, the medical field changed the medical treatment paradigm from the method of treatment based on the knowledge and experience of doctors in the past to the form of receiving the help of high-precision medical intelligence based on medical data. In addition, due to the spread of non-face-to-face treatment due to the COVID-19 pandemic, it is expected that the era of telemedicine, in which patients will be treated by doctors at home rather than hospitals, will soon come. It can be said that artificial medical intelligence plays a big role at the center of this paradigm shift in prevention-centered treatment rather than treatment. Based on big data, this paper analyzes the current status of artificial intelligence technology for chronic disease patients, market trends, and domestic and foreign company trends to predict the expected effect and future development direction of artificial intelligence technology for chronic disease patients. In addition, it is intended to present the necessity of developing digital therapeutics that can provide various medical services to chronically ill patients and serve as medical support to clinicians.

• Journal of the Korean Data and Information Science Society
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• v.19 no.2
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• pp.577-585
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• 2008

This paper suggests a marginal probability model for analyzing repeated polytomous response data when some factors are nested in others in treatment structures on a larger experimental unit. As a repeated measures factor, time is considered on a smaller experimental unit. So, two different experiment sizes are considered. Each size of experimental unit has its own design structure and treatment structure, and the marginal probability model can be constructed from the structures for each size of experimental unit. Weighted least squares(WLS) methods are used for estimating fixed effects in the suggested model.

• Journal of Oral Medicine and Pain
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• v.41 no.3
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• pp.110-117
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• 2016

Purpose: The purpose of this study is to determine factors influencing the duration of occlusal appliance (OA) treatment for patients with temporomandibular joint (TMJ) internal derangement. Methods: Ninety patients were included for this study, who satisfied the following including criteria: (i) those who were diagnosed as disc displacement of TMJ by taking magnetic resonance imaging (MRI) and (ii) those who were finished OA treatment. The subjects were classified into three groups according to the period of OA treatment: (i) early response group (<6 months), (ii) moderate response group (6 months-1 year), and (iii) delayed response group (>1 year). Demographic data, data from chief complaints and past history of temporomandibular disorder, data from clinical examination and diagnostic imaging including panoramic view and TMJ MRI were compared among groups. One-way ANOVA and chi-square analysis were used to test statistical significance. Results: There were no significant differences in demographic data, data from chief complaints and TMJ imaging. However, only the prevalence of oral parafunctional habits including bruxism, clenching, and unilateral chewing showed significant differences among groups. Conclusions: Oral parafunctional habits could be factors to influence the duration of OA treatment in the patients with TMJ internal derangement.