• Journal of Korean Society of Forest Science
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• v.111 no.2
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• pp.201-223
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• 2022

Currently, species extinctions are increasing due to climate change and continued anthropogenic impact. We selected 300 species for conservation with emphasis on plants co-occurring in the Baekdudaegan area, which is a large ecological axis of Korea. We aimed to investigate the vegetation community and environmental characteristics of Zabelia tyaihyonii in the limestone habitat among the target plant species in the Baekdudaegan region to derive effective conservation strategies. In Danyang-gun, Yeongwol-gun, and Jecheon-si, we selected 36 investigation sites where Z. tyaihyonii was present. We investigated the vegetation, flora, soil and physical environment. We also found notable plants such as Thalictrum petaloideum, Sillaphyton podagraria, and Neillia uekii at the investigation sites. We classified forest vegetation community types into 4 vegetation units and 7 species group types. With canonical correspondence analysis (CCA) of the vegetation community and habitat factors, we determined the overall explanatory power to be 75.2%, and we classified the environmental characteristics of the habitat of Z. tyaihyonii into a grouping of three. Among these, we detected a relationship between the environmental factors elevation, slope, organic matter, rock ratio, pH, potassium, and sodium. We identified numerous rare and endemic plants, including Thalictrum petaloideum, in the investigation site, and determined that these groups needed to be preserved at the habitat level. In the classification of the vegetation units analyzed based on the emerging plants and the CCA, we reaffirmed the uniqueness and specificity of the vegetation community in the habitat of Z. tyaihyonii. We anticipate that our results will be used as scientific evidence for the empirical conservation of the native habitats of Z. tyaihyonii.

• Journal of agricultural medicine and community health
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• v.47 no.3
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• pp.166-180
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• 2022

Objective: This study evaluated the effects of a non-face-to-face obesity management program, implemented during the pandemic. Methods: The non-face-to-face obesity management program used the Intervention mapping protocol (IMP). The program was put into effect over the course of eight weeks, from September 14 to November 13, 2020 in 48 overweight and obese adults, who applied to participate through the Daegu Citizen Health Support Center. Results: IMP was first a needs assessment was conducted; second, goal setting for behavior change was established; third, evidence-based selection of arbitration method and performance strategy was performed; fourth, program design and validation; fifth, the program was run; and sixth, the results were evaluated. The average weight after participation in the program was reduced by 1.2kg, average WC decreased by 3cm, and average BMI decreased by 0.8kg/m² (p<0.05). The results of the health behavior survey showed a positive improvement in lifestyle factors, including average daily intake calories, fruit intake, and time spent in walking exercise before and after participation in the program. A statistically significant difference was seen (p<0.05). The satisfaction level for program process evaluation was high, at 4.57±0.63 point. Conclusion: The non-face-to-face obesity management program was useful for obesity management for adults in communities, as it enables individual counseling by experts and active participation through self-body measurement and recording without restriction by time and place. However, the program had some restrictions on participation that may relate to the age of the subject, such as skill and comfort in using a mobile app.

• Journal of Bio-Environment Control
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• v.31 no.4
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• pp.504-512
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• 2022

To examine the distribution of internal solar radiation within various locations in multi-span greenhouses, the solar radiation, light transmittance, and accumulated radiation at the central and lateral sections were analyzed by dividing 8:30 to 12:30 in the morning and 12:35 to 16:30 in the afternoon. The growth and yield of tomatoes within these sections were also compared. In the morning, the solar radiation of the central section and the side section was 275.2 W·m^-2 and 314.9 W·m^-2, while in the afternoon, it was 314.9 W·m^-2 and 313.9 W·m^-2, respectively. The light transmittance and accumulated radiation were also low, confirming the low distribution of solar radiation in the central (connecting) section of the multi-span greenhouses. The growth survey revealed no significant difference. The final yield of tomatoes per plant was 4,828 g in the central section and 4,851 g in the lateral section, but there was no significant difference in the central section compared to the lateral section by 0.5%. However, the amount of solar radiation as per time in the central section is higher than the light compensation point, 60 W·m^-2, and slightly lower than the light saturation point of tomatoes, i.e., 281 W·m^-2. The results of this study can help in greenhouse design based on the insolation environment.

• Journal of the Korean Society of Marine Environment & Safety
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• v.28 no.spc
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• pp.30-36
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• 2022

A sensor is needed to continuously and automatically measure the change in HNS concentration in industrial facilities that directly discharge to the sea after water treatment. The basic function of the sensor is to be able to detect ppb levels even at room temperature. Therefore, a method for increasing the sensitivity of the existing sensor is proposed. First, a method for increasing the conductivity of a film using a conductive carbon-based additive in a nanoparticle thin film and a method for increasing ion adsorption on the surface using a catalyst metal were studied.. To improve conductivity, carbon black was selected as an additive in the film using ITO nanoparticles, and the performance change of the sensor according to the content of the additive was observed. As a result, the change in resistance and response time due to the increase in conductivity at a CB content of 5 wt% could be observed, and notably, the lower limit of detection was lowered to about 250 ppb in an experiment with organic solvents. In addition, to increase the degree of ion adsorption in the liquid, an experiment was conducted using a sample in which a surface catalyst layer was formed by sputtering Au. Notably, the response of the sensor increased by more than 20% and the average lower limit of detection was lowered to 61 ppm. This result confirmed that the chemical resistance sensor using metal oxide nanoparticles could detect HNS of several tens of ppb even at room temperature.

• Journal of the korean academy of Pediatric Dentistry
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• v.50 no.2
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• pp.168-178
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• 2023

Objectives: This study aimed to compare the physical properties and antibacterial effectiveness of iodoform based root filling pastes, Vitapex^® and Metapex^®, with sodium iodide root filling paste (NaI paste) for primary teeth. Materials and Methods: The physical properties (flowability, film thickness, radiopacity) of the pastes were evaluated according to ISO 6876:2012. The antibacterial activity against Enterococcus faecalis strain (ATCC 6538) was evaluated using a direct contact test. Results: There was no significant statistical difference (p > 0.05) observed in the flow and film thickness of NaI paste when compared to the currently available root canal filling materials. The average flow capacities for Vitapex^®, Metapex^®, and NaI paste were 15.40 mm, 21.25 mm, and 20.01 mm, respectively. The average film thickness for Vitapex^®, Metapex^®, and NaI paste were 33.3 ㎕, 22.6 ㎕, and 25.0 ㎕, respectively. However, NaI paste showed lower radiopacity than the existing materials, and this difference was statistically significant (p < 0.05) NaI paste demonstrated higher antimicrobial activity than the available materials, and this difference was also statistically significant (p < 0.05). Conclusion: Compared to the existing commercialized root canal filling materials, NaI paste exhibited similar performance in terms of flow and film thickness, and superior antimicrobial activity against E. faecalis. Hence, NaI paste could be a promising root filling material for primary teeth and may be a potential alternative to existing materials.

• Journal of the Korean Society of Earth Science Education
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• v.16 no.2
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• pp.210-223
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• 2023

This study developed elementary and middle school career education programs linked to science subjects and local natural resources, and explored learning effects and implications for developing and operating career programs. In order to achieve the research purpose, a 10-hour career education program using local natural and social resources was developed and applied to 25 elementary and middle school students in rural areas. As a result of the study, most of the elementary and middle school students who participated in this study were not well aware of the natural and social resource value of the area where they lived. Therefore, when developing and operating a regional-based career education program for elementary and middle school students in rural areas, it is necessary to operate a separate teaching/learning activity time so that students can fully know the natural and social information and resource values of the region. In addition, in order to enhance students' participation and interest in career education programs, it is necessary to organize the operation of the program in groups, not individuals, and to guide students in detail by dividing the program's performance process into several sub-steps. Finally, the core material of regional-linked career education-related programs focused more on their own content, that is, agricultural products grown by parents, and future job settings were higher in start-ups that directly operate companies such as travel agencies and manufacturing companies. Given the recent emphasis on career education in the curriculum, it is suggested that local students should pay more attention to finding materials with local resource value in the field of geoscience, which is closely related to natural resources, and developing and operating them as career education programs linked to local resources.

• Economic Analysis
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• v.26 no.1
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• pp.84-132
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• 2020

A central bank infers market expectations of future yields based on yield curves. The central bank needs to precisely understand the changes in market expectations of future yields in order to have a more effective monetary policy. This need explains why a range of models have attempted to produce yield curves and market expectations that are as accurate as possible. Alongside the development of bond markets, the interconnectedness between them and macroeconomic factors has deepened, and this has rendered understanding of what macroeconomic variables affect yield curves even more important. However, the existence of various theories about determinants of yields inevitably means that previous studies have applied different macroeconomics variables when estimating yield curves. This indicates model uncertainties and naturally poses a question: Which model better estimates yield curves? Put differently, which variables should be applied to better estimate yield curves? This study employs the Dynamic Nelson-Siegel Model and takes the Bayesian approach to variable selection in order to ensure precision in estimating yield curves and market expectations of future yields. Bayesian variable selection may be an effective estimation method because it is expected to alleviate problems arising from a priori selection of the key variables comprising a model, and because it is a comprehensive approach that efficiently reflects model uncertainties in estimations. A comparison of Bayesian variable selection with the models of previous studies finds that the question of which macroeconomic variables are applied to a model has considerable impact on market expectations of future yields. This shows that model uncertainties exert great influence on the resultant estimates, and that it is reasonable to reflect model uncertainties in the estimation. Those implications are underscored by the superior forecasting performance of Bayesian variable selection models over those models used in previous studies. Therefore, the use of a Bayesian variable selection model is advisable in estimating yield curves and market expectations of yield curves with greater exactitude in consideration of the impact of model uncertainties on the estimation.

• Journal of the Korean Institute of Landscape Architecture
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• v.51 no.2
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• pp.103-119
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• 2023

Since the Korean government has decided to apply the policy of BIM (Building Information Modeling) to the entire construction industry, it has experienced a positive trend in adoption and utilization. BIM can reduce workloads by building model objects into libraries that conform to standards and enable consistent quality, data integrity, and compatibility. In the domestic architecture, civil engineering, and the overseas landscape architecture sectors, many BIM library standardization studies have been conducted, and guidelines have been established based on them. Currently, basic research and attempts to introduce BIM are being made in Korean landscape architecture field, but the diffusion has been delayed due to difficulties in application. This can be addressed by enhancing the efficiency of BIM work using standardized libraries. Therefore, this study aims to provide a starting point for discussions and present a classification system for objects and attribute information that can be referred to when creating landscape libraries in practice. The standardization of landscape BIM library was explored from two directions: object classification and attribute information items. First, the Korean construction information classification system, product inventory classification system, landscape design and construction standards, and BIM object classification of the NLA (Norwegian Association of Landscape Architects) were referred to classify landscape objects. As a result, the objects were divided into 12 subcategories, including 'trees', 'shrubs', 'ground cover and others', 'outdoor installation', 'outdoor lighting facility', 'stairs and ramp', 'outdoor wall', 'outdoor structure', 'pavement', 'curb', 'irrigation', and 'drainage' under five major categories: 'landscape plant', 'landscape facility', 'landscape structure', 'landscape pavement', and 'irrigation and drainage'. Next, the attribute information for the objects was extracted and structured. To do this, the common attribute information items of the KBIMS (Korean BIM Standard) were included, and the object attribute information items that vary according to the type of objects were included by referring to the PDT (Product Data Template) of the LI (UK Landscape Institute). As a result, the common attributes included information on 'identification', 'distribution', 'classification', and 'manufacture and supply' information, while the object attributes included information on 'naming', 'specifications', 'installation or construction', 'performance', 'sustainability', and 'operations and maintenance'. The significance of this study lies in establishing the foundation for the introduction of landscape BIM through the standardization of library objects, which will enhance the efficiency of modeling tasks and improve the data consistency of BIM models across various disciplines in the construction industry.

• Journal of Internet Computing and Services
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• v.24 no.2
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• pp.19-26
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• 2023

Humans have adapted and evolved to natural light. However, as humans stay in indoor longer in modern times, the problem of biorhythm disturbance has been induced. To solve this problem, research is being conducted on lighting that reproduces the correlated color temperature(CCT) of natural light that varies from sunrise to sunset. In order to reproduce the CCT of natural light, multiple LED light sources with different CCTs are used to produce lighting, and then a control index DB is constructed by measuring and collecting the light characteristics of the combination of input currents for each light source in hundreds to thousands of steps, and then using it to control the lighting through the light characteristic matching method. The problem with this control method is that the more detailed the steps of the combination of input currents, the more time and economic costs are incurred. In this paper, an LED lighting control method that applies interpolation and combination calculation based on the minimum spectral power distribution information for each light source is proposed to reproduce the CCT of natural light. First, five minimum SPD information for each channel was measured and collected for the LED lighting, which consisted of light source channels with different CCTs and implemented input current control function of a 256-steps for each channel. Interpolation calculation was performed to generate SPD of 256 steps for each channel for the minimum SPD information, and SPD for all control combinations of LED lighting was generated through combination calculation of SPD for each channel. Illuminance and CCT were calculated through the generated SPD, a control index DB was constructed, and the CCT of natural light was reproduced through a matching technique. In the performance evaluation, the CCT for natural light was provided within the range of an average error rate of 0.18% while meeting the recommended indoor illumination standard.

• Journal of Intelligence and Information Systems
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• v.28 no.1
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• pp.263-286
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• 2022

This study acquires NBA statistical information for a total of 32 years from 1990 to 2022 using web crawling, observes variables of interest through exploratory data analysis, and generates related derived variables. Unused variables were removed through a purification process on the input data, and correlation analysis, t-test, and ANOVA were performed on the remaining variables. For the variable of interest, the difference in the mean between the groups that advanced to the playoffs and did not advance to the playoffs was tested, and then to compensate for this, the average difference between the three groups (higher/middle/lower) based on ranking was reconfirmed. Of the input data, only this year's season data was used as a test set, and 5-fold cross-validation was performed by dividing the training set and the validation set for model training. The overfitting problem was solved by comparing the cross-validation result and the final analysis result using the test set to confirm that there was no difference in the performance matrix. Because the quality level of the raw data is high and the statistical assumptions are satisfied, most of the models showed good results despite the small data set. This study not only predicts NBA game results or classifies whether or not to advance to the playoffs using machine learning, but also examines whether the variables of interest are included in the major variables with high importance by understanding the importance of input attribute. Through the visualization of SHAP value, it was possible to overcome the limitation that could not be interpreted only with the result of feature importance, and to compensate for the lack of consistency in the importance calculation in the process of entering/removing variables. It was found that a number of variables related to three points and errors classified as subjects of interest in this study were included in the major variables affecting advancing to the playoffs in the NBA. Although this study is similar in that it includes topics such as match results, playoffs, and championship predictions, which have been dealt with in the existing sports data analysis field, and comparatively analyzed several machine learning models for analysis, there is a difference in that the interest features are set in advance and statistically verified, so that it is compared with the machine learning analysis result. Also, it was differentiated from existing studies by presenting explanatory visualization results using SHAP, one of the XAI models.