• The Journal of the Korean dental association
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• v.22 no.7 s.182
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• pp.621-633
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• 1984

The possibility of expanding the linear range of the Kinesiograph was studied using a nonferromagnetic mechanical positioning device. The magnet was moved in linear steps of 5 mm through three planes parallel to the frame work carrying the sensors within working range of a 3 cm wide by 4 cm deep by 5 cm high three dimensional lattice and a matrix of 693 data points was achieved. For each data point, the three Kinesiograph outputs were associated with the values of actual position. Once three coordinates of observed values were known, actual values could be determined. A computer program was specially written in Fortran to deal with this work. Because each dat point was 5 mm apart from each other, there would be 480 cubes with 8 data points Further refinement of the system is possible using a smaller interval between each data point. In conclusion, a theoretical model was presented which, by means of computer support, would allow the absolute measurement of jaw position over the entire range of functional jaw movements.

• Health Policy and Management
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• v.25 no.3
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• pp.197-206
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• 2015

Background: The purpose of this study was to propose a method for developing a measure of hospital-wide all-cause risk-standardized readmissions using administrative claims data in Korea and to discuss further considerations in the refinement and implementation of the readmission measure. Methods: By adapting the methodology of the United States Center for Medicare & Medicaid Services for creating a 30-day readmission measure, we developed a 6-step approach for generating a comparable measure using Korean datasets. Using the 2010 Korean National Health Insurance (NHI) claims data as the development dataset, hierarchical regression models were fitted to calculate a hospital-wide all-cause risk-standardized readmission measure. Six regression models were fitted to calculate the readmission rates of six clinical condition groups, respectively and a single, weighted, overall readmission rate was calculated from the readmission rates of these subgroups. Lastly, the case mix differences among hospitals were risk-adjusted using patient-level comorbidity variables. The model was validated using the 2009 NHI claims data as the validation dataset. Results: The unadjusted, hospital-wide all-cause readmission rate was 13.37%, and the adjusted risk-standardized rate was 10.90%, varying by hospital type. The highest risk-standardized readmission rate was in hospitals (11.43%), followed by general hospitals (9.40%) and tertiary hospitals (7.04%). Conclusion: The newly developed, hospital-wide all-cause readmission measure can be used in quality and performance evaluations of hospitals in Korea. Needed are further methodological refinements of the readmission measures and also strategies to implement the measure as a hospital performance indicator.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.3C
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• pp.157-170
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• 2006

Downhole method is considered as giving a little unreliable Vs profile when the signal to noise ratio(S/N) is low and the travel time information is erroneous although it is economical and ease of operation. Direct method has been applied for obtaining adequate result in this case. But it is difficult to determine optimum result by using direct method which is subjective and considering straight ray path. Therefore, in this paper, Mean Refracted Ray Path Method(MRM) was proposed, which is automated and considering refracted ray path. Artificial travel time data adding some travel time error was generated by forward modeling based on Snell's Law and travel time data was also obtained from numerical signal traces using FEM modelling. Using these travel time data, reliability of MRM was verified in the manner of comparing the results determined by MRM with the model. Finally, proposed method was applied to the real field data and it was considered as improved method for obtaining the optimum result in downhole seismic method.

• The Journal of the Korea institute of electronic communication sciences
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• v.19 no.1
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• pp.189-196
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• 2024

Frequent false positives alarm from the Intelligent Selective Control System have raised significant concerns. These persistent issues have led to declines in operational efficiency and market credibility among agents. Developing a new model or replacing the existing one to mitigate false positives alarm entails substantial opportunity costs; hence, improving the quality of the training dataset is pragmatic. However, smaller organizations face challenges with inadequate capabilities in dataset collection and refinement. This paper proposes an automatic human pose data collection system centered around a human pose estimation model, utilizing camera-based sensor fusion techniques and edge devices. The system facilitates the direct collection and real-time processing of field data at the network periphery, distributing the computational load that typically centralizes. Additionally, by directly labeling field data, it aids in constructing new training datasets.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.13 no.3
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• pp.157-163
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• 2013

Data mining is a useful technology that can support new discoveries based on the pattern analysis and a variety of linkages between data, and currently is utilized in various fields such as finance, marketing, medical. In this paper, we propose an effective utilization method of data based on analysis of spatial data mining. We make use of basic data of foreigners living in Seoul. However, the data has some features distinguished from other areas of data, classification as sensitive information and legal problem such as personal information protection. So, we use the basic statistical data that does not contain personal information. The main features and contributions of the proposed method are as follows. First, we can use Big Data as information through a variety of ways and can classify and cluster Big Data through refinement. Second. we can use these kinds of information for decision-making of future and new patterns. In the performance evaluation, we will use visual approach through graph of themes. The results of performance evaluation show that the analysis using data mining technology can support new discoveries of patterns and results.

• Journal of Broadcast Engineering
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• v.2 no.2
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• pp.206-215
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• 1997

We pror.a;e a H.263-based video ceder with two-layer ocalability. The bare layer is ceded by using the default H.263 axling algorithms to achieve high compresred video data and the enhanced layer is axied by enhanced axling such as HVS-based quantization updating. The enhanced layer contains only arled refinement data for the OCT coefficients of the bare layer. Bitstream syntax and semantics for enhancement layer are designed and quantizer design using the HVS is pror.ooed. Data from the two layers are combined after inverse quantization and inverse OCT prcx:esses in the deaxier. We show with e~rirrental results that the pror.a;ed layered arlee achieves comparable picture quality with non-layered arlee at bitrates of 30 kbr;s or less. Overhead information for the bitstream layer can 00 limited to less than 0.5 kbits/frame.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.30 no.4
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• pp.593-603
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• 2020

The advent of malicious code has increased exponentially due to the spread of malicious code generation tools in accordance with the development of the network, but there is a limit to the response through existing malicious code detection methods. According to this situation, a machine learning-based malicious code detection method is evolving, and in this paper, the feature of data is extracted from the PE header for machine-learning-based malicious code detection, and then it is used to automate the malware through autoencoder. Research on how to extract the indicated features and feature importance. In this paper, 549 features composed of information such as DLL/API that can be identified from PE files that are commonly used in malware analysis are extracted, and autoencoder is used through the extracted features to improve the performance of malware detection in machine learning. It was proved to be successful in providing excellent accuracy and reducing the processing time by 2 times by effectively extracting the features of the data by compressively storing the data. The test results have been shown to be useful for classifying malware groups, and in the future, a classifier such as SVM will be introduced to continue research for more accurate malware detection.

• Journal of the Korean Society of Costume
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• v.52 no.8
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• pp.137-149
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• 2002

This study was made to investigate the differences in Korean woman's perceived makeup image and self-consciousness according to their expectation level in socio-psychological effect of makeup, and to gather information needed for the better understanding of cosmetics consumers and more effective marketing activities of cosmetics industries. Normative-descriptive survey method using questionnaire was employed for the present study. The survey was conducted in August 2001 and the sample consisted of 942 women between the ages of 18 and 50 residing in Seoul and Kyungi province. Data were analyzed by SPSS package. Factor analysis, ANOVA, and MANOVA were employed for the analysis of the data. The results are as follows : (1) Six factors emerged from the data related to the category of expected socio-psychological effect of makeup. Those factors were named as "increasing positiveness", "refreshment", "covering weakness", "self-expression", "consideration for others", and "the tool for self-change". Four factors were found in the category of makeup image, and the factors were named as "refinement", "nobility", "favorable impression ", and "personality ". (2) There was a tendency that those who highly expect the socio-psychological effect of makeup have more positive self-image. Considering this differences in self-image according to the level of expected socio-psychological effect of makeup. service activities for the consumers' positive opinion and attitude to the effect of makeup are needed, and it seems that those service activities will have a good influence on the consumers' emotional health. (3) Subjects with higher level of social anxiety showed higher expectations in refreshment, covering weakness and self-expression. Considering this trend, marketers have to make an constant effort for the variety of cosmetics and makeup manner by which consumers satisfy their expectation in makeup. It seems that the satisfaction of their expectation on the help of makeup effect will contribute to lessen social anxiety, and to get emotional stability. (4) Subjects with higher personal self-anxiety showed higher expectations of the effect. "increase of positiveness". Therefore, if the product advertisement imply the content of increasing positiveness effect of makeup, it might appeal more easily to their consumers.imply the content of increasing positiveness effect of makeup, it might appeal more easily to their consumers.

• Journal of Korean Medical classics
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• v.33 no.4
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• pp.21-32
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• 2020

Objectives : Pulse descriptions in Korean Medical texts are comprised of combinations of pulse terminology, where various combinations of pulse terminology are used to describe disease symptoms. For Korean Medical doctors and professionals, however, it is impossible to identify the entirety of pulse description combinations, and their understanding is mostly limited to those learned from classical texts studied individually. Methods :This research was carried out by using Access of Microsoft Office 365 in Windows 10 of Microsoft. Pulse descriptions were extracted from the text, 『Euijongsonik』. In the final stages, the automatically extracted list of pulse descriptions was refined through [excluded terminology of pulse description]. Results : The PC environment of this research was Intel Core i7-1065G7 CPU 1.30GHz, with 8GB of RAM and a Windows 10 64bit operation system. Out of 6,115 verses 6,497 descriptions were primarily extracted, and after a refinement process, the final list contained 5,507 pulse descriptions. Conclusions : Based on the assumption that classical texts are available in data form to be processed by programs, current research methodology demonstrated that it was more efficient in regards to time and man power to create a pulse description database compared to when the researcher manually created one.

• The Journal of the Korea Contents Association
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• v.21 no.4
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• pp.205-219
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• 2021

The present study identified determinants to user acceptance of artificial intelligence(AI)-based news anchor. Our conceptual model included three constructs of ability, benevolence, and integrity to determine whether these three constructs are predictive of trust perceived from AI news anchor. This work further examined the influences of social presence, anthropomorphism, perceived usefulness, understanding as well as trust as immediate determinants to user acceptance. The conceptual model was validated on survey data collected from 513 respondents. A series of scale refinement process was conducted by the examination of data normality, common method bias, structure of latent variables as well as internal consistency. In addition, a confirmatory factor analysis was performed to assess the extent to which the sample data collected from survey study measures the constructs adequately. The results from the analysis of structural equation model indicated that, (1) two constructs of ability and integrity were found to be significantly predictive of perceived trust, and (2) anthropomorphism, perceived usefulness, and trust emerged as significant and positive predictors of user acceptance of AI-based news anchor.