• The korean journal of orthodontics
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• v.48 no.1
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• pp.23-29
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• 2018

Objective: In accordance with the changing demographics in the United States, orthodontists working on various ethnic populations should be more conscious when using the standardized profile analyses for the African American patient. The objective of this study was to examine whether the perception of lip protrusiveness in modern African American faces has changed. For this purpose, we investigated the most favorable African American lip profile using the opinions of 10 experienced and 10 newly trained younger orthodontists. Methods: Attractiveness was converted to a number on visualized analog scales. Comparative ranks on 16 African American profiles, with focus on lip protrusiveness and thickness, were made among the groups. Mixed-effects linear regression models were fit and group differences were estimated. Results: Younger orthodontists favored a more protrusive lip profile, and the variance in their perceptions was narrower than those of older orthodontists. Measurements related to upper lip protrusion showed the strongest correlation to attractiveness (r = -0.82). The association with attractiveness decreased linearly as the protrusiveness of the upper lip increased. Steiner's E-line was the most influential reference for determining the level of attractiveness for the older orthodontists, whereas upper lip protrusion was the most influential factor for the young orthodontists. Conclusions: An adequate level of lip protrusiveness and thickness should be essential for maintaining attractive esthetics in African American patients. Yet, a new set of standards for prominent lips in this population is necessary to reflect the current trend in the concept of a beautiful face in the modern world.

• Transactions of the Korean hydrogen and new energy society
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• v.22 no.4
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• pp.534-545
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• 2011

This paper describes the evaluation of kinetic parameters for pyrolysis and carbon char oxidation of residual oil. The non-isothermal pyrolysis of residual oil was carried out with TGA (Thermo-Gravimetric Analyzer) at heating rate of 2, 5, 10 and $20^{\circ}C/min$ up to $800^{\circ}C$ under N2 atmosphere. The first order and nth order pyrolysis models were used to fit the experimental data, and the nth order model was turned out to follow the experimental data more precisely than the first order model. For carbon char oxidation experiment, TGA and four heating rates used in pyrolysis experiment were also adapted. The kinetic parameters for the residual carbon char particle were obtained with three char oxidation model, that is, volume reaction, grain and random pore model. Among them, the random pore model described the char oxidation behaviour quite well, compared to other two models. The non-linear regression method was used to obtain kinetic parameters for both pyrolysis and carbon char oxidation of residual oil.

• Journal of the Korean Society of Marine Environment & Safety
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• v.25 no.2
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• pp.244-250
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• 2019

We investigated the relationship between morphological characteristics and individual dry weight to develop a method for estimating the individual dry weight of sheet form macroalgae: Ulva australis, Ulva linza, Pachymeniopsis lanceolata, and Pyropia yezoensis. In Total, 319 thalli of various sizes were collected at six sites from February 2017 to December 2018. An interspecific allometric exponent of 0.28 was found for length-biomass allometry in four sheet form macroalgae, corresponding to a 1/4-power law for primary producers. The relationships between surface area and individual dry weight, as well as between individual fresh weight and individual dry weight, were found to fit significantly using linear regression equations. This explained 94-99 % of individual dry weight, indicating that surface area and individual fresh weight can be used to accurately estimate individual dry weight. We propose the use of this method when experimental processes do not allow individual dry weight to be measured directly, so researchers can save both time and expense.

• Research in Community and Public Health Nursing
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• v.30 no.2
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• pp.206-216
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• 2019

Purpose: This study is to investigate the low back pain, social support, impediment in daily living activities and to identify factors affecting impediment in elderly farmer' daily living activities. Methods: The participants were 128 elderly farmers who had received nerve block. Data were collected using a structured questionnaire from February to March, 2018. They were analyzed using t-test, ANOVA, pearson's correlation coefficient, and linear multiple regression. Results: The score of low back pain was $6.27{\pm}1.69$ (10 points), that of social support $2.92{\pm}0.76$ (1~5 points), and that of impediment in activity of daily living $2.01{\pm}0.82$ (0~5 points). Factors affecting impediment in activity of daily living were found to include age (p=.017), daily hours of farm work (p<.001), fear for the nerve block (p<.001), low back pain (p<.001), and social support (p<.001); the explanatory power of these variables was 58.8%. Conclusion: This study has found the controllable factors affecting impediment in activity of daily living among the rural elderly engaging in farm work include low back pain, social support, and daily farming hours. Therefore, to reduce impediment in activity of daily living among them, it is necessary to develop nursing interventions that can improve impediment in activity of daily living through reduction of daily farming hours using local resources. It is also desirable to improve their health status by reducing low back pain, and develop and apply social supports with health education programs that fit the local resources and the needs of the rural elderly.

• Journal of Astronomy and Space Sciences
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• v.39 no.2
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• pp.43-50
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• 2022

The unified scheme of Seyfert galaxies hypothesizes that the observed differences between the two categories of Seyfert galaxies, type 1 (Sy1) and type 2 (Sy2) are merely due to the difference in the orientation of the toroidal shape of the obscuring material in the active galactic nuclei. We used in this paper, a sample consisting of 120 Seyfert galaxies at 1.40 × 10⁹ Hz in radio, 2.52 × 10¹⁷ Hz in X-ray and 2.52 × 10²³ Hz in γ-ray luminosities observed by the Fermi Large Area Telescope (Fermi-LAT) in order to test the unified scheme of radio-quiet Seyfert galaxies. Our main results are as follows: (i) We found that the distributions of multiwave luminosities (L_radio, L_X-ray, and L_γ-ray) of Sy1 and Sy2 are completely overlapped with up to a factor of 4. The principal component analysis result reveals that Sy1 and Sy2 also occupy the same parameter spaces, which agrees with the notion that Sy1 and Sy2 are the same class objects. A Kolmogorov-Smirnov test performed on the sub-samples indicates that the null hypothesis (both are from the same population) cannot be rejected with chance probability p ~ 0 and separation distance K = 0.013. This result supports the fact that there is no statistical difference between the properties of Sy1 and Sy2 (ii) We found that the coefficient of the best-fit linear regression equation between the common properties of Sy1 and Sy2 is significant (r > 0.50) which plausibly implies that Sy1 and Sy2 are the same type of objects observed at different viewing angle.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.6
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• pp.1892-1912
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• 2022

With the massive demand and growth of cloud computing, virtualization plays an important role in providing services to end-users efficiently. However, with the increase in services over Cloud Computing, it is becoming more challenging to manage and run multiple Virtual Machines (VMs) in Cloud Computing because of excessive power consumption. It is thus important to overcome these challenges by adopting an efficient technique to manage and monitor the status of VMs in a cloud environment. Reduction of power/energy consumption can be done by managing VMs more effectively in the datacenters of the cloud environment by switching between the active and inactive states of a VM. As a result, energy consumption reduces carbon emissions, leading to green cloud computing. The proposed Efficient Dynamic VM Scheduling approach minimizes Service Level Agreement (SLA) violations and manages VM migration by lowering the energy consumption effectively along with the balanced load. In the proposed work, VM Scheduling for Efficient Dynamically Migrated VM (VMS-EDMVM) approach first detects the over-utilized host using the Modified Weighted Linear Regression (MWLR) algorithm and along with the dynamic utilization model for an underutilized host. Maximum Power Reduction and Reduced Time (MPRRT) approach has been developed for the VM selection followed by a two-phase Best-Fit CPU, BW (BFCB) VM Scheduling mechanism which is simulated in CloudSim based on the adaptive utilization threshold base. The proposed work achieved a Power consumption of 108.45 kWh, and the total SLA violation was 0.1%. The VM migration count was reduced to 2,202 times, revealing better performance as compared to other methods mentioned in this paper.

• Journal of People, Plants, and Environment
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• v.24 no.6
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• pp.629-638
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• 2021

Background and objective: This study was conducted to develop diameter growth models for thinned Quercus glauca Thunb. (QGT) stands to inform production goals for treatment and provide the information necessary for the systematic management of this stands. Methods: This study was conducted on QGT stands, of which initial thinning was completed in 2013 to develop a treatment system. To analyze the tree growth and trait response for each thinning treatment, forestry surveys were conducted in 2014 and 2021, and a one-way analysis of variance (ANOVA) was executed. In addition, non-linear least squares regression of the PROC NLIN procedure was used to develop an optimal diameter growth model. Results: Based on growth and trait analyses, the height and height-to-diameter (H/D) ratio were not different according to treatment plot (p > .05). For the diameter of basal height (DBH), the heavy thinning (HT) treatment plot was significantly larger than the control plot (p < .05). As a result of the development of diameter growth models by treatment plot, the mean squared error (MSE) of the Gompertz polymorphic equation (control: 2.2381, light thinning: 0.8478, and heavy thinning: 0.8679) was the lowest in all treatment plots, and the Shapiro-Wilk statistic was found to follow a normal distribution (p > .95), so it was selected as an equation fit for the diameter growth model. Conclusion: The findings of this study provide basic data for the systematic management of Quercus glauca Thunb. stands. It is necessary to construct permanent sample plots (PSP) that consider stand status, location conditions, and climatic environments.

• Korean Journal of Artificial Intelligence
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• v.11 no.4
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• pp.9-13
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• 2023

In this study, we explored the potential of integrating interactive AI callbot technology into the medical consultation domain as part of a broader service development initiative. Aimed at enhancing patient satisfaction, the AI callbot was designed to efficiently address queries from hospitals' primary users, especially the elderly and those using phone services. By incorporating an AI-driven callbot into the hospital's customer service center, routine tasks such as appointment modifications and cancellations were efficiently managed by the AI Callbot Agent. On the other hand, tasks requiring more detailed attention or specialization were addressed by Human Agents, ensuring a balanced and collaborative approach. The deep learning model for voice recognition for this study was based on the Transformer model and fine-tuned to fit the medical field using a pre-trained model. Existing recording files were converted into learning data to perform SSL(self-supervised learning) Model was implemented. The ANN (Artificial neural network) neural network model was used to analyze voice signals and interpret them as text, and after actual application, the intent was enriched through reinforcement learning to continuously improve accuracy. In the case of TTS(Text To Speech), the Transformer model was applied to Text Analysis, Acoustic model, and Vocoder, and Google's Natural Language API was applied to recognize intent. As the research progresses, there are challenges to solve, such as interconnection issues between various EMR providers, problems with doctor's time slots, problems with two or more hospital appointments, and problems with patient use. However, there are specialized problems that are easy to make reservations. Implementation of the callbot service in hospitals appears to be applicable immediately.

• Journal of Korea Technology Innovation Society
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• v.17 no.1
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• pp.45-67
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• 2014

National Innovative Capability (NIC) is an important decisive factor where economic growth is concerned. As such, it is very important to measure and manage NIC. The composite index approach is one of the widely used approaches to measuring NIC, but there have been insufficient reviews of its feasibility and reliability. This paper conducted an analysis of the feasibility and reliability of the report on the last three years (i.e. 2011 through 2013) of the Innovation Union Scoreboard (IUS) of the EU, which is the most representative means of measuring NIC. It turned out that its reliability meets the recommended criteria as a result of Chronbach's alpha-based test of the models of IUS-related composite index. However, neither the absolute fit index nor the incremental fit index was found to meet the recommended criteria in a construct validity analysis. It also turned out that predictive validity is very low as a result of panel linear regression analysis of sectors and items of IUS-related composite index. This paper presents a number of considerations to be made when measuring national innovative capability using the composite index approach, as well as major policy suggestions based on the results of the analysis.

• Land and Housing Review
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• v.12 no.2
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• pp.47-59
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• 2021

This study aims to review the trends of the population outflows in the metropolitan area of Busan and to investigate the factors that affect population out-migration to the Seoul metropolitan area. The following variables are considered for analysis: traditional population movement variables and quality of life variables, such as population, society, employment, housing, culture, safety, medical care, greenery, education, and childcare. The 'domestic population movement data', provided by the MDIS of the National Statistical Office, was used for this research. Out of the total of 57 million population movement data in the period 2012 - 2017, population outmigration from Busan to the Seoul metropolitan area was extracted. Independent variables were drawn from public data sources in accordance with the temporal and spatial settings of the study. The multiple linear regression model was specified based on the dataset, and the fit of the model was measured by the p-value, and the values of Adjusted R2, Durbin-Watson analysis, and F-statistics. The results of the analysis showed that the variables that have a significant effect on population movement from Busan to the Seoul metropolitan area were as follows: 'single-person households', 'the elderly population', 'the total birth rate', 'the number of companies', 'the number of employees', 'the housing sales price index', 'cultural facilities', and 'the number of students per teacher'. More positive (+) influences of the population out-movement were observed in areas with higher numbers of single-person households, lowers proportions of the elderly, lower numbers of businesses, higher numbers of employees, higher numbers of housing sales, lower numbers of cultural facilities, and lower numbers of students. The findings suggest that policies should enhance the environments such as quality jobs, culture, and welfare that can retain young people within Busan. Improvements in the quality of life and job creation are critical factors that can mitigate the outflows of the Busan residents to the Seoul metropolitan area.