• Journal of Service Research and Studies
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• v.12 no.2
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• pp.65-79
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• 2022

Non-face-to-face classes continue due to Covid-19. There have been e-learning classes since the past, but the difference is that the current non-face-to-face classes are blended classes that combine real-time and recording classes or combine face-to-face and non-face classes. It is also characterized by being able to self-filmed or choose various lecture platforms in a place other than a dedicated studio. The advantages of non-face-to-face classes can be learned beyond time and space, and repetitive viewing and learning speed can be adjusted. Greening classes have no time and place constraints, and real-time classes have the advantage of high communication effects with learners. Evaluating whether non-face-to-face classes provide sufficient quality compared to face-to-face classes or e-learning will be necessary if branded classes are considered for post Covid. In this paper, for the evaluation of the service quality of non-face-to-face classes, the essential attributes desired by the instructors were derived from the viewpoint of Kano quality attributes and a quality improvement plan was proposed. After expressing the degree of functions that non-face-to-face classes should have on the X-axis and the satisfaction of learners on the Y-axis, 23 quality attributes were classified into 6 quality dimensions. In addition, satisfaction coefficient, dissatisfaction coefficient, and customer satisfaction improvement index were derived. As a result, 50% of learners were satisfied with non-face-to-face classes, but the preference was slightly higher than satisfaction, suggesting the sustainability of non-face-to-face classes. In terms of the customer satisfaction improvement index, the ranking of attributes with the largest increase in satisfaction when improving class quality was as follows. Professors' quick answers to learners' questions, content that can fully explain the subject, what the professor explains easily, develop high-quality content that can be learned on mobile phones, fairness of attendance checks, and real-time classes should start on time.

• Korean Journal of Plant Resources
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• v.36 no.2
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• pp.172-180
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• 2023

In the current study, four groups; control, 500, 1000, and 2000 mg/L, were treated to investigate the effects of physiological and growth characteristics on Machilus thunbergii under various fertilization levels. As a result of the physiological response to the fertilization treatment, the fertilized group demonstrated relatively higher levels of A, ITE, WUEi, V_camx, PI_abs, and SFI_abs in comparison to the control. The best photosynthetic mechanism was most clearly seen at 1000 mg/L, which involved gas exchange through active stomatal opening and closing. For a productive photosynthetic mechanism. As seen in the growth response of M. thunbergii to fertilization treatment, the fertilized group has significantly higher height, DRC, leaf dry weight, stem dry weight, total dry weight, LWR, and SWR than the control group. A healthy seedling quality index was particularly evident at 1000 mg/L, and other growth indicators were also at a decent level. 500 mg /L also demonstrated growth characteristics that were comparable to those at 1000 mg/L. As a result, M. thunbergii featured the best physiological and growth characteristics in response to the fertilization treatment at 1000 mg/L, and 500 mg/L also showed a similar trend, which is considered to be a good option from an economical perspective.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.67 no.4
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• pp.253-264
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• 2022

In this study, we investigated the occurrence of viral diseases in the early growth stage of soybean to establish management practices. We collected 83 soybean samples showing abnormal symptoms, approximately 3-4 weeks after seeding in the breeding field of the National Institute of Crop Science. Viruses were detected in the collected samples using reverse transcription polymerase chain reaction (RT-PCR) and metatranscriptome analysis of all those samples. The incidence of viral diseases in the field was less than 1% overall and up to 50% in certain cultivars and lines. RT-PCR and metatranscriptome analysis detected Soybean yellow mottle mosaic virus (SYMMV), Soybean mosaic virus (SMV), Soybean yellow common mosaic virus, Peanut stunt virus, and soybean geminivirus A (SGVA). Among these detected viruses, SYMMV and SMV were identified as major viruses causing infection in the early growth stage of soybean, with detection rates of 53.7% and 42.6%, respectively. Soybeans infected with SYMMV showed typical mosaic symptoms, whereas those infected with SMV showed a variety of symptoms such as mosaic, mottle, stunt, and chlorotic spots. Transmission characteristics of these viruses are variable, such that SMV is primarily transmitted by seeds, whereas SYMMV could be transmitted by insects, soil, and seeds. In this study, SGVA was detected in the early growth stage of soybean, and research on the current status and its effects on soybean after the early growth stage should be conducted.

• Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
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• 2001.06a
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• pp.4107-4107
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• 2001

Previous works have shown the viability of NIRS technology for the prediction of fatty acids in Iberian pig fat, but although the resulting equations showed high precision, in the predictions of new samples important fluctuations were detected, greater with the time passed from calibration development to NIRS analysis. This fact makes the use of NIRS calibrations in routine analysis difficult. Moreover, this problem only appears in products like fat, that show spectrums with very defined absorption peaks at some wavelengths. This circumstance causes a high sensibility to small changes of the instrument, which are not perceived with the normal checks. To avoid these inconveniences, the software WinISI 1.04 has a mathematic algorithm that consist of create a “Repeatability File”. This file is used during calibration development to minimize the variation sources that can affect the NIRS predictions. The objective of the current work is the evaluation of the use of a repeatability file in quantitative NIRS analysis of Iberian pig fat. A total of 188 samples of Iberian pig fat, produced by COVAP, were used. NIR data were recorded using a FOSS NIRSystems 6500 I spectrophotometer equipped with a spinning module. Samples were analysed by folded transmission, using two sample cells of 0.1mm pathlength and gold surface. High accuracy calibration equations were obtained, without and with repeatability file, to determine the content of six fatty acids: miristic (SECV$\sub$without/=0.07% r$^2$$\sub$without/=0.76 and SECV$\sub$with/=0.08% r$^2$$\sub$with/=0.65), Palmitic (SECV$\sub$without/=0.28 r$^2$$\sub$without/=0.97 and SECV$\sub$with/=0.24% r$^2$$\sub$with/=0.98), palmitoleic (SECV$\sub$without/=0.08 r$^2$$\sub$without/=0.94 and SECV$\sub$with/=0.09% r$^2$$\sub$with/=0.92), Stearic (SECV$\sub$without/=0.27 r$^2$$\sub$without/=0.97 and SECV$\sub$with/=0.29% r$^2$$\sub$with/=0.96), oleic (SECV$\sub$without/=0.20 r$^2$$\sub$without/=0.99 and SECV$\sub$with/=0.20% r$^2$$\sub$with/=0.99) and linoleic (SECV$\sub$without/=0.16 r$^2$$\sub$without/=0.98 and SECV$\sub$with/=0.16% r$^2$$\sub$with/=0.98). The use of a repeatability file like a tool to reduce the variation sources that can disturbed the prediction accuracy was very effective. Although in calibration results the differences are negligible, the effect caused by the repeatability file is appreciated mainly when are predicted new samples that are not in the calibration set and whose spectrum were recorded a long time after the equation development. In this case, bias values corresponding to fatty acids predictions were lower when the repeatability file was used: miristic (bias$\sub$without/=-0.05 and bias$\sub$with/=-0.04), Palmitic (bias$\sub$without/=-0.42 and bias$\sub$with/=-0.11), Palmitoleic (bias$\sub$without/=-0.03 and bias$\sub$with/=0.03), Stearic (bias$\sub$without/=0.47 and bias$\sub$with/=0.28), oleic (bias$\sub$without/=0.14 and bias$\sub$with/=-0.04) and linoleic (bias$\sub$without/=0.25 and bias$\sub$with/=-0.20).

• Journal of Korea Water Resources Association
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• v.56 no.2
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• pp.103-113
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• 2023

The river confluence is a section in which two rivers with different topographical and hyrodynamic characteristics are combined into one, and it is a section in which rapid flow, inflow of sediments, and hydrological topographic changes occur. In the confluence section, the flow of fluid occurs due to the difference in density due to the type of material or temperature difference, which is called a density flow. It is necessary to accurately measure and observe the confluence section including a certain section of the main stream and tributaries in order to understand the mixing behavior of the water body caused by the density difference. A comprehensive analysis of this water mixture can be obtained by obtaining flow field and flow rate information, but there is a limit to understanding the mixing of water bodies with different physical properties and water quality characteristics of rivers flowing with stratigraphic flow. Therefore, this study attempts to grasp the density flow through the water temperature distribution in the confluence section. Among the extensive data of the river, vertical data and water surface data were acquired, and through this, the stratification phenomenon of the confluence was to be confirmed. It was intended to analyze the mixed pattern of the confluence by analyzing the water mixing pattern according to the water temperature difference using the vertical data obtained by measuring the repair volume by installing the ADCP on the side of the boat and measuring the real-time concentration using YSI. This study can supplement the analysis results of the existing water quality measurement in two dimensions. Based on the comparative analysis, it will be used to investigate the current status of stratified sections in the water layer and identify the mixing characteristics of the downstream section of the river.

• Journal of Nutrition and Health
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• v.56 no.1
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• pp.54-69
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• 2023

Purpose: Proteins are major components of the body and essential nutrients for proper growth and development. However, studies on protein intake in children and adolescents are insufficient. A few previous studies have reported the relationship with growth indicators, but results vary depending on the source of protein. Therefore, the current study investigates the relationship between protein intake and overweight and obesity among children and adolescents in Korea. Methods: Based on the 2014-2019 Korea National Health and Nutrition Examination Survey, 5,567 children and adolescents aged 6-18 years, who participated in a 24-hour dietary recall with information on height and weight, were included in this study. Protein intake was estimated as percentage of total energy (% of energy) and was classified into animal and plant protein according to the food source. Overweight and obesity were defined using the 2017 pediatric and adolescent growth chart. Results: Total protein intake of the subjects was estimated as 14.5% of total energy (animal protein 8.3% and plant protein 6.3%). The group with the highest total protein intake had a higher odds ratio (OR) of overweight/obesity than those with the least protein intake (OR, 1.36, 95% confidence interval (CI), 1.10-1.67, p for trend = 0.003). When classified by food source, the group with the highest animal protein intake had a significantly higher OR of overweight/obesity than subjects with the lowest intake (OR, 1.30, 95% CI, 1.05-1.61, p for trend = 0.016). However, plant protein was not significantly associated with overweight/obesity. Conclusions: These findings suggest that a high intake of animal protein in children and adolescents increases the risk of being overweight and obese. In order to develop normal growth and prevent obesity in the future, it is necessary to determine an appropriate protein intake level through nutrition education programs and prospective studies on balanced protein intake.

• The Korean Journal of Coaching Psychology
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• v.7 no.1
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• pp.59-89
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• 2023

In this study, change motivation for growth and development is defined as 'the power to set a specific action direction for change based on the perception of one's current behavior in order to achieve a goal that one considers important, and to be willing to act'. In addition, the purpose of this study was to develop and validate a scale to measure the motivation for change for growth and development of general adults. To develop preliminary questions, interviews were conducted with 7 coaching experts and 9 experienced coaches, and an open-ended questionnaire was conducted with 55 adults. Afterwards, 7 factors and 83 questions were selected through three rounds of item classification and content validity verification, and a preliminary survey was conducted targeting 321 general adults, and 42 items, 4 factors, were derived through exploratory factor analysis. did Finally, the main survey was conducted with 631 adults in order to verify the validity of the construct concept of the change motivation scale and the validity of the criterion. Divided into two groups, 315 people in group 1 conducted exploratory factor analysis and 316 people in group 2 conducted confirmatory factor analysis to verify the concept of change motivation scale. As a result of the factor analysis of Group 1, it was found that the 3 factor structure consisting of 31 items was appropriate, and as a result of the confirmatory factor analysis of Group 2, the goodness of fit of the modified model of the 3 factor structure was confirmed, which motivated change. The construct validity of the scale was demonstrated. As a result of analyzing the correlations with various variables for the analysis of convergent validity and criterion-related validity of the Motivation for Change scale, each of the three factors was found to be significantly related to most variables. Finally, the significance, implications and limitations of this study, and future research were discussed.

• Journal of Service Research and Studies
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• v.13 no.3
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• pp.172-189
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• 2023

This study investigated the potential contribution of ChatGPT, a massive language and information model, in the decision-making process of public design policies, focusing on the characteristics inherent to public design. Public design utilizes the principles and approaches of design to address societal issues and aims to improve public services. In order to formulate public design policies and plans, it is essential to base them on extensive data, including the general status of the area, population demographics, infrastructure, resources, safety, existing policies, legal regulations, landscape, spatial conditions, current state of public design, and regional issues. Therefore, public design is a field of design research that encompasses a vast amount of data and language. Considering the rapid advancements in artificial intelligence technology and the significance of public design, this study aims to explore how massive language and information models like ChatGPT can contribute to public design policies. Alongside, we reviewed the concepts and principles of public design, its role in policy development and implementation, and examined the overview and features of ChatGPT, including its application cases and preceding research to determine its utility in the decision-making process of public design policies. The study found that ChatGPT could offer substantial language information during the formulation of public design policies and assist in decision-making. In particular, ChatGPT proved useful in providing various perspectives and swiftly supplying information necessary for policy decisions. Additionally, the trend of utilizing artificial intelligence in government policy development was confirmed through various studies. However, the usage of ChatGPT also unveiled ethical, legal, and personal privacy issues. Notably, ethical dilemmas were raised, along with issues related to bias and fairness. To practically apply ChatGPT in the decision-making process of public design policies, first, it is necessary to enhance the capacities of policy developers and public design experts to a certain extent. Second, it is advisable to create a provisional regulation named 'Ordinance on the Use of AI in Policy' to continuously refine the utilization until legal adjustments are made. Currently, implementing these two strategies is deemed necessary. Consequently, employing massive language and information models like ChatGPT in the public design field, which harbors a vast amount of language, holds substantial value.

• Journal of the Korean Association of Geographic Information Studies
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• v.26 no.3
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• pp.52-64
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• 2023

As cities continue to develop rapidly, overcrowding, pollution, and urban sanitation problems arise, and the need to separate conflicting uses is emerging. From this perspective, there is no disagreement that urban land use should be planned. Therefore, all activities in land space must be predicted in advance and planned so that land use can be rationally established. This study used the constructed data to compare and analyze the use distribution characteristics of residential, commercial, and industrial areas in Busan Metropolitan City to identify the building area status, total floor area, and floor area ratio by use zone in districts and counties in Busan Metropolitan City. As a result, it was found that the residential area accounted for the largest proportion of the area by use zone at 51%, and that the residential area accounted for the largest proportion at 63% of the total floor area by use zone. And the analysis was conducted using a specialization coefficient that can identify regional characteristics based on land use composition ratio. Because it is difficult to determine the trend of the entire region just by counting the absolute value of the area, the area composition ratio was calculated and compared. Looking at the residential facilities among the specialization coefficients by use area, it is above 1.0 except for Gijang-gun, Sasang-gu, Saha-gu, and Jung-gu. Commercial facilities are over 1.0 except for Gijang-gun, Gangseo-gu, Nam-gu, Sasang-gu, and Saha-gu. Looking at industrial facilities, you can see that the industrial complex distribution area is Gangseo-gu (2.5), Gijang-gun (1.22), Sasang-gu (2.06), and Saha-gu (1.64). In addition, it was found that business facilities and educational welfare facilities were evenly distributed. Land use analysis was conducted through simulation of the current status of building heights according to each elevation in each use area and the height of buildings in each use area. In general, areas over 80m account for more than 43% of Busan City, showing that the distribution of use areas is designated in areas with high altitude due to the influence of topographical conditions.

• Journal of Intelligence and Information Systems
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• v.29 no.3
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• pp.185-209
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• 2023

With the advent of the 4th industrial revolution, various technologies have received much attention. Technologies related to the 4th industry include the Internet of Things (IoT), big data, artificial intelligence, virtual reality (VR), 3D printers, and robotics, and these technologies are often converged. In particular, the robotics field is combined with technologies such as big data, artificial intelligence, VR, and digital twins. Accordingly, much research using robotics is being conducted, which is applied to distribution, airports, hotels, restaurants, and transportation fields. In the given situation, research on human-robot interaction is attracting attention, but it has not yet reached the level of user satisfaction. However, research on robots capable of perfect communication is steadily being conducted, and it is expected that it will be able to replace human emotional labor. Therefore, it is necessary to discuss whether the current human-robot interaction technology can be applied to business. To this end, this study first examines the trend of human-robot interaction technology. Second, we compare LDA (Latent Dirichlet Allocation) topic modeling and BERTopic topic modeling methods. As a result, we found that the concept of human-robot interaction and basic interaction was discussed in the studies from 1992 to 2002. From 2003 to 2012, many studies on social expression were conducted, and studies related to judgment such as face detection and recognition were conducted. In the studies from 2013 to 2022, service topics such as elderly nursing, education, and autism treatment appeared, and research on social expression continued. However, it seems that it has not yet reached the level that can be applied to business. As a result of comparing LDA (Latent Dirichlet Allocation) topic modeling and the BERTopic topic modeling method, it was confirmed that BERTopic is a superior method to LDA.