• Journal of Electrical Engineering and Technology
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• v.5 no.3
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• pp.400-406
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• 2010

This paper deals with parameter tuning of the Power System Stabilizer (PSS) for 612 MVA thermal power plants in the KEPCO system and its validation in a field test. In this paper, the selection of parameters, such as lead-lag time constants for phase compensation and system gain, is optimized using linear and eigenvalue analyses. This is then verified through the time-domain transient stability analysis. In the next step, the performance of PSS is finally verified by the generator's on-line field test. After the field test, measured and simulated data are also compared to prove the effectiveness of the models used in the simulations.

• Genomics & Informatics
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• v.4 no.3
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• pp.110-117
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• 2006

In microarray technology, many diverse experimental features can cause biases including RNA sources, microarray production or different platforms, diverse sample processing and various experiment protocols. These systematic effects cause a substantial obstacle in the analysis of microarray data. When such data sets derived from different experimental processes were used, the analysis result was almost inconsistent and it is not reliable. Therefore, one of the most pressing challenges in the microarray field is how to combine data that comes from two different groups. As the novel trial to integrate two data sets with batch effect, we simply applied standardization to microarray data before the significant gene selection. In the gene selection step, we used new defined measure that considers the distance between a gene and an ideal gene as well as the between-slide and within-slide variations. Also we discussed the association of biological functions and different expression patterns in selected discriminative gene set. As a result, we could confirm that batch effect was minimized by standardization and the selected genes from the standardized data included various expression pattems and the significant biological functions.

• Economic and Environmental Geology
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• v.33 no.2
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• pp.129-138
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• 2000

The various types of geohazards like landslides resulted from civil construction (i.e. highway construction) must of analysed considering all the possible influential factor systematically. Thus, by using GIS, slope stability can be evaluated, and it can be used as a data for further detailed investigation. So the aim of this study is to present a data for decision making in selecting suitable point for remediation. For analysing slope instability, through appropriate definition and classification, landslide mechanism must be understood. In building GIS model, the selection of appropriate factors and their rating system should be made. For this, the characteristics and the mechanism of landslide have to be understood. And suitable coverage should be chosen for the model considering the slope conditions. In this study, field investigation in lst and 2nd Section, Chung-ang highway was carried out. From the field data, GIS model on slope instability was created. 5 coverages were used for it. From the result of this study, 12 unstable sections were found out and more detailed investigation is needed there.

• International Journal of Computer Science & Network Security
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• v.21 no.3
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• pp.177-184
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• 2021

All over the world, people are affected by many chronic diseases and medical practitioners are working hard to find out the symptoms and remedies for the diseases. Many researchers focus on the feature detection of the disease and trying to get a better health recommendation system. It is necessary to detect the features automatically to provide the most relevant solution for the disease. This research gives the framework of Health Recommendation System (HRS) for identification of relevant and non-redundant features in the dataset for prediction and recommendation of diseases. This system consists of three phases such as Pre-processing, Feature Selection and Performance evaluation. It supports for handling of missing and noisy data using the proposed Imputation of missing data and noise detection based Pre-processing algorithm (IMDNDP). The selection of features from the pre-processed dataset is performed by proposed ensemble-based feature selection using an expert's knowledge (EFS-EK). It is very difficult to detect and monitor the diseases manually and also needs the expertise in the field so that process becomes time consuming. Finally, the prediction and recommendation can be done using Support Vector Machine (SVM) and rule-based approaches.

• Journal of Information Science Theory and Practice
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• v.10 no.2
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• pp.86-101
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• 2022

This research aimed at studying the factors that influence new media exposure of political news by youths in Isan society in Thailand. The target group comprised 1,200 individuals, obtained from multi-stage sampling from undergraduate students in Isan's autonomous universities, governmental universities, and private institutions. The data collection tool was a questionnaire, the content of which was validated by experts. The reliability of the tool was tested by the formula for Cronbach's alpha coefficient, which yielded a reliability of 0.83. Multiple regression analysis was applied to analyze the data. The results, regarding factors influencing the channels for political news exposure, showed that channels for political news exposure were mostly influenced by inner drives, followed by importance in political news exposure, influence from social networks, and specific characteristics of the Internet. This could explain the variation of channels for political news exposure at 46.5%. In terms of factors influencing political news selection, it was found that political news selection was influenced mostly from social networks, followed by inner drives, benefits from political news exposure, specific characteristics of the Internet, and the field of study. The variation of the political news selection could be explained at 44.6%. These results elaborate on the current situation in Thailand, especially in Isan region, where youths in higher education are playing an increasing role in demonstrating their political stance through various political activities.

• Korea Journal of Hospital Management
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• v.23 no.4
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• pp.1-14
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• 2018

Purpose : Customers with loyalty are very important to hospitals for sustainable growth in their medical market. Individuals with loyalty are likely to visit same hospital repeatedly when they need medical services. This study was to identify factors associated with selection of specialty hospitals among customers with loyalty. Methods : The subjects of this study were 735 inpatients in 22 specialty hospitals in 6 designated fields(joints, spine, colorectal-anal, obstetrics and gynecology, ophthalmology, otolaryngology). Customer types classified as customers with high loyalty, neutral customers, and customers with low loyalty according to net promoter score(NPS). Factor analysis was conducted to classify 22 hospital selection factors into some similar properties. Logistic regression analysis was conducted to confirm the selection factors related to loyal customers. Findings : Most of specialty hospitals received high NPS of 8 points or higher in all the designated fields. Five factors associated with selection of specialty hospital are (1) hospital facilities and convenience, (2) trust in doctor and hospital, (3) rapidness of treatment, (4) hospital awareness, and (5) accessibility. As a result of logistic regression analysis, selection factors related to loyal customers were 'hospital facilities and convenience', 'trust in doctor and hospital' and 'rapidness of treatment'. Differences in the degree of importance of three selection factors by customer types appeared for each designated field. Practical Implications : This study confirms the high level of patient experience among inpatients of specialty hospitals. Factors associated with selection of hospital among inpatients with loyalty are 'facilities and convenience of hospitals', 'trust of doctor and hospital' and 'rapidness of treatment'. This study will be meaningful as basic data to systematically enhance the roles and functions of the health care system and to provide securing competitiveness according to designated fields in the management aspect of specialty hospitals.

• Journal of Korean Dental Hygiene Science
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• v.4 no.1
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• pp.29-37
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• 2021

Background: The selection of an occupation is typically based on individuals' personalities and the characteristics of occupations, which significantly affect occupational consciousness. The present study aimed to enhance the occupational achievement level of and provide fundamental data for student counseling in order to develop competitive professional workers by understanding the occupational consciousness of freshmen and motivating them as dental hygienists with career development plans, as freshmen majoring in dental hygiene eventually play a significant role in the field of dentistry as dental hygienists. Methods: The surveys were distributed to 160 freshmen in the dental hygiene department and were subsequently collected. The data from 142 surveys were used for analysis, as 18 surveys were excluded due to insincere responses. The survey contents included questions related to major selection and satisfaction, including motives for selecting a dental hygiene major, prior knowledge on a dental hygiene major and a career as a dental hygienist, satisfaction level of the major, and reasons for dissatisfaction in cases if applicable, as well as questions related to occupational consciousness, including career prospects for dental hygienists, opinions on the occupation, and conditions of job selection. Results: High employment rate with good salary level ranked highest (43.7%) among motives to apply the dental hygiene major, followed by the desire to be a professional worker (21.1%) and recommendation by acquaintances. Of those who responded, 50.7% indicated a normal level of satisfaction with the major, and 69.9% responded that they had prior knowledge regarding the dental hygiene major and/or field of dental hygiene. These results may be due to youth unemployment and the occurrence of job preparation immediately after students enter university, which is a result of the difficulty in job seeking. In terms of career prospects, 48.6% of students responded with "growing a little bit," followed by "growing a lot" (28.9%), "no difference from now" (21.1%), and "other" (1.4%). Regarding opinions on the occupation, 65.5% responded that occupation was an tool with which to make and income or a living, 23.2% responded that occupation was for dreams and self-realization, and 11.3% responded that occupation was for success in life and maintaining social status. Regarding the conditions of job selection, the responses included that the workplace had good working conditions (39.4%), good interpersonal relationships (21.8%), and a higher salary (18.3%). This may reflect the change in work ethics among university students, according to the trend of the times. Conclusion: Based on the results of the present study, we found that educational guidance to enhance the level of satisfaction with the major, and career guidance to understand and apply the clear vision and long-term job security are necessary.

• Journal of Industrial Convergence
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• v.20 no.2
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• pp.1-9
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• 2022

As the need for improvement of transparency and fairness in the selection of national R&D projects has been continuously raised, we analyzed the impact on the evaluation selection results by evaluation indexes for The land transportation technology commercialization support project and searched for ways to improve indexes using the analysis results. As for the research data, it were applied as selection results of new R&D projects and evaluation indexes in two fields(SME innovation and start-up) in 2021. Logistic regression analysis is used for the influence of each evaluation indexes on the evaluation result, and for the regression model, evaluation indexes with low influence are removed in advance through artificial neural network multiple perceptron analysis to improve the reliability of the analysis results. As a result of the analysis, in the field of SME innovation, the influence of the evaluation index on the workforce planning was the lowest and the influence of the appropriateness of commercialization promotion plan was the highest. In the start-up field, the influence of the evaluation indexes for technology development suitability, marketability, and suitability for carrying out the project were estimated to be similar to each other, and the influence of the technology evaluation index was found to be the lowest. The analysis results of this thesis suggest the need for continuous improvement of selection and evaluation indexes, and by using the analysis results to select a fair R&D institution according to the selection of appropriate indexes, it will be possible to contribute to deriving excellent research results and fostering excellent companies in the field of land transportation.

• Journal of Research and Publication Ethics
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• v.5 no.1
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• pp.7-11
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• 2024

Purpose: This study seeks to discuss research ethics, not only the academic honesty and sincerity that researchers who study aviation services academically should have, but also the direction of the moral aspects that are fundamentally required as researchers. Additionally, this study seeks to examine the realistic problems of research related to the aviation service industry, a field of social science. Lastly, focusing on research ethics in the aviation service field, we will look at the theoretical background and the problems in the actual research field, and draw implications based on this. Research design, data and methodology: This study conducted an exploratory study through a selection process based on research ethics topics and research ethics related to the aviation service industry. Results: Efforts to systematize research ethics in research areas related to the aviation service industry, which is a field of social science, require efforts to expand the scope of systematization of research ethics related to the aviation service industry by referring to systemization efforts in other academic fields. In addition, specific systemization efforts will be needed through cooperation between universities, research institutes, and academic organizations. Also, concrete systematization efforts will be needed through cooperation between universities and academic organizations.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.50 no.4
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• pp.268-275
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• 2005

Early predictions of crop yields call provide information to producers to take advantages of opportunities into market places, to assess national food security, and to provide early food shortage warning. The objectives of this study were to identify the most useful parameters for estimating yields and to compare two model selection methods for finding the 'best' model developed by multiple linear regression. This research was conducted in two 65ha corn/soybean rotation fields located in east central South Dakota. Data used to develop models were small temporal variability information (STVI: elevation, apparent electrical conductivity $(EC_a)$, slope), large temporal variability information (LTVI : inorganic N, Olsen P, soil moisture), and remote sensing information (green, red, and NIR bands and normalized difference vegetation index (NDVI), green normalized difference vegetation index (GDVI)). Second order Akaike's Information Criterion (AICc) and Stepwise multiple regression were used to develop the best-fitting equations in each system (information groups). The models with $\Delta_i\leq2$ were selected and 22 and 37 models were selected at Moody and Brookings, respectively. Based on the results, the most useful variables to estimate corn yield were different in each field. Elevation and $EC_a$ were consistently the most useful variables in both fields and most of the systems. Model selection was different in each field. Different number of variables were selected in different fields. These results might be contributed to different landscapes and management histories of the study fields. The most common variables selected by AICc and Stepwise were different. In validation, Stepwise was slightly better than AICc at Moody and at Brookings AICc was slightly better than Stepwise. Results suggest that the Alec approach can be used to identify the most useful information and select the 'best' yield models for production fields.