• Journal of The Korean Association For Science Education
• /
• v.39 no.4
• /
• pp.535-544
• /
• 2019

In order to find out whether the traditional mass media in our society are sufficiently functioning as a vehicle of providing scientific information to the public outside the school education, public perception of science articles in mass media and scientific terms used in high frequency in science articles have been examined. To investigate the public perception on science articles, a questionnaire was constructed about the usefulness, importance, access frequency, and understanding of science articles. The questionnaires were conducted in areas with high flow populations such as train stations or subway stations. A total of 425 responses were used for analysis. In order to extract high frequency scientific terms used in science articles, two television companies and two newspapers were designated as target media, and their texts on science articles reported over the last 17 years were collected to investigate the frequency of scientific terms used. Based on the frequency, we conducted the self-report comprehension test for the top 100 scientific terms. The results of this study show that the public in our society has relatively high perception of the importance and usefulness of science articles, however, reading and understanding the articles seems to be somewhat difficult. In addition, the scientific terminology used in science articles has a high degree of comprehension for those of higher education, natural sciences majors, and men. In addition, scientific terms with high understanding degree were characterized according to gender, age, educational background, and field of major.

• Wind and Structures
• /
• v.28 no.2
• /
• pp.71-87
• /
• 2019

The yaw and interference effects of blades affect aerodynamic performance of large wind turbine system significantly, thus influencing wind-induced response and stability performance of the tower-blade system. In this study, the 5MW wind turbine which was developed by Nanjing University of Aeronautics and Astronautics (NUAA) was chosen as the research object. Large eddy simulation on flow field and aerodynamics of its wind turbine system with different yaw angles($0^{\circ}$, $5^{\circ}$, $10^{\circ}$, $20^{\circ}$, $30^{\circ}$ and $45^{\circ}$) under the most unfavorable blade position was carried out. Results were compared with codes and measurement results at home and abroad, which verified validity of large eddy simulation. On this basis, effects of yaw angle on average wind pressure, fluctuating wind pressure, lift coefficient, resistance coefficient,streaming and wake characteristics on different interference zone of tower of wind turbine were analyzed. Next, the blade-cabin-tower-foundation integrated coupling model of the large wind turbine was constructed based on finite element method. Dynamic characteristics, wind-induced response and stability performance of the wind turbine structural system under different yaw angle were analyzed systematically. Research results demonstrate that with the increase of yaw angle, the maximum negative pressure and extreme negative pressure of the significant interference zone of the tower present a V-shaped variation trend, whereas the layer resistance coefficient increases gradually. By contrast, the maximum negative pressure, extreme negative pressure and layer resistance coefficient of the non-interference zone remain basically same. Effects of streaming and wake weaken gradually. When the yaw angle increases to $45^{\circ}$, aerodynamic force of the tower is close with that when there's no blade yaw and interference. As the height of significant interference zone increases, layer resistance coefficient decreases firstly and then increases under different yaw angles. Maximum means and mean square error (MSE) of radial displacement under different yaw angles all occur at circumferential $0^{\circ}$ and $180^{\circ}$ of the tower. The maximum bending moment at tower bottom is at circumferential $20^{\circ}$. When the yaw angle is $0^{\circ}$, the maximum downwind displacement responses of different blades are higher than 2.7 m. With the increase of yaw angle, MSEs of radial displacement at tower top, downwind displacement of blades, internal force at blade roots all decrease gradually, while the critical wind speed decreases firstly and then increases and finally decreases. The comprehensive analysis shows that the worst aerodynamic performance and wind-induced response of the wind turbine system are achieved when the yaw angle is $0^{\circ}$, whereas the worst stability performance and ultimate bearing capacity are achieved when the yaw angle is $45^{\circ}$.

• 교육공학연구
• /
• v.33 no.1
• /
• pp.105-135
• /
• 2017

The purpose of this study is to clarify conceptually the difference of instructional coaching, instructional supervision, and instructional consulting by analyzing their own characteristics. The practices for instructional improvement are common in that fundamental objectives are improvement of instruction and development of teacher's professionalism in instruction. However, each area changed according to the social flow and the demands of the educational field and created a unique activity system. So, in order to get rid of this mixed use of these terms, it is meaningful to distinguish the concepts, attributes, and areas of each activity. The specific study questions were 1) what is the origin of coaching, supervision, and consulting? 2) how are instructional coaching, instructional supervision, and instructional consulting defined in existing research in korea? 3) how can we conceptually distinguish instructional coaching, instructional supervision, and instructional consulting? Based on reviewing various existing studies, First, this study investigated the conceptual origins and lexicons of coaching, supervision, and consulting, respectively, in addition reviewd the prior studies conducted in Korea with regard to instructional coaching, instructional supervision, and instructional consulting, and summarized how each concept is defined according to the researcher. Second, this study compared each two concept with another one. Finally, the existing definitions of instructional coaching, instructional supervision, and instructional consulting were analyzed to find out the inherent and common attributes of each concept. In conclusion, this study suggest that the concept of instructional consulting needs to be redefined to better reflect the characteristics of activities, and that studies that rethink the relationship between instructional coaching and instructional supervision are needed.

• The Journal of the Korea Contents Association
• /
• v.21 no.3
• /
• pp.441-453
• /
• 2021

Recently, the untact healthcare industry due to COVID-19 has been attracting attention, and the telemedicine industry based on medical information has become a field of the healthcare industry receiving attention. However, in Korea, due to obstacles in the legal system, telemedicine is still illegal between doctors and patients. In the case of neighboring China, the reality is the opposite of the recent rapid growth of the telemedicine industry under the leadership of the government. This study looks at this from the perspective of the industrial innovation system on the grounds that telemedicine is an industry and innovative technology needs to be changed to clarify the difference between domestic and Chinese telemedicine industries. As a result of analyzing China's telemedicine industry on the seven sub-divisions of demand conditions, innovators, networks et al., Such as seizing appropriate opportunities for demand driving effects and appropriate communication between economic actors were identified as major success factors. This researcher proposes the following suggestions. first, it conforms to the current digital New Deal policy flow, and conducts a demand survey on the change in demand for medical services in the 4th Industrial Revolution and the Untact Era. For the introduction, a plan to conduct a demand survey for the public and second, second, a plan to grow and intensively foster digital high-tech medical care as a new industry was suggested.

• Journal of Korea Water Resources Association
• /
• v.55 no.1
• /
• pp.99-109
• /
• 2022

This study was intended to suggest the applicability of stepped boulder fishway using the concept of traditional boulder weir, focusing on the problems of existing concrete pool-and-weir fishways installed in mountain streams. To achieve this purpose, a stepped boulder fishway was designed and constructed as a pilot project in consideration of ascending capacity of the selected target fishes. Under the given discharge conditions, the hydraulic characteristics of the fishway were investigated in the field, and the characteristics and ascending capacity of the fishes were compared and analyzed. The fishway had a short length and steep slope, but the mean drops between each baffle were the range of 0.15 to 0.29 m, and this range satisfied the limit condition of about 0.40 m, which was in the limit of the drop that target fishes can ascend. The mean velocities of each baffle and pool were 0.82 to 0.87 m/sec and 0.13 to 0.24 m/sec. This result satisfied the conditions of burst speed (10 to 30 times of body length) and mean velocity of the resting pool (7 to 25% of burst speed) for target fishes. Since the bottom surface of the pool formed of boulders had a gentle reverse slope and rotational flow did not occur, the efficiency of fishway can be increased, and it will also be possible to solve the maintenance problem by flushing bed materials.

• Journal of Korea Entertainment Industry Association
• /
• v.14 no.5
• /
• pp.131-146
• /
• 2020

This research is based on social flow that is in need of sports welfare that diagnoses the delivery system of sports program pass that is typical business of national sports welfare services and operation structure, and analyze the supplier, operator, beneficiary and all that is related to business from multilateral aspects, therefore seek for operation systems for provision systems of sports welfare services. To clearly grasp the operating mechanisms of service provision system that is happening in real field, there were in-depth interview done by the 18 people of suppliers, operators, and beneficiaries that are the main participants of business, and through which drew an ideal agreed point for sports welfare services to get in the right direction. The result of this study is as following: First, based on the limited government budget for the compilation of budget for the business of sports welfare services it is found that there is need of constructing a pragmatic service provision system that can bring maximum of efficiency. Second, voucher that was introduced for market logic application and greater transparency of the business of sports welfare services has a complex structure that it is in need of simplification of structure which that is well fit with its characteristics. Third, for convenience enlargement in administration and management, make management policy of provision system be reflected and therefore enlarge the independence of management and secure the power of negotiation regarding fee savings through centralized budget management.

• Journal of Korean Society of Forest Science
• /
• v.112 no.3
• /
• pp.374-381
• /
• 2023

The travel time of flash floods along mountain streams is mainly governed by reach-average velocity, rather than by the point velocity of the locations of interest. Reach-average velocity is influenced by various factors such as stream geometry, streambed materials, and the hydraulic roughness of streams. In this study, the reach-average velocity in mountain streams was measured for storm periods using rhodamine dye tracing. The point cloud data obtained from a LiDAR survey was used to extract the average hydraulic roughness height, such as R_a, R_max, and R_z. The size distribution of the streambed materials (D₅₀, D₈₄) was also considered in the estimation of the roughness height. The field experiments revealed that the reach-average velocities had a significant relationship with flow discharges (v = 0.5499Q^0.6165 ), with an R² value of 0.77. The root mean square error in the roughness height of the R_a-based estimation (0.45) was lower than those of the other estimations (0.47-1.04). Among the parameters for roughness height estimation, the R_a -based roughness height was the most reliable and suitable for developing the reach-average velocity equation for estimating the travel time of flood waves in mountain streams.

• Journal of Korean Society of Forest Science
• /
• v.112 no.3
• /
• pp.340-351
• /
• 2023

Landslides are major natural geological hazards that cause enormous property damage and human casualties annually. The vulnerability of mountainous areas to landslides is further exacerbated by the impacts of climate change. Soil depth is a crucial parameter in landslide and debris flow analysis, and plays an important role in the evaluation of watershed hydrological processes that affect slope stability. An accurate method of estimating soil depth is to directly investigate the soil strata in the field. However, this requires significant amounts of time and money; thus, numerous models for predicting soil depth have been proposed. However, they still have limitations in terms of practicality and accuracy. In this study, 71 seismic survey results were collected from domestic mountainous areas to estimate soil depth on hill slopes. Soil depth was estimated on the basis of a shear wave velocity of 700 m/s, and a database was established for slope angle, elevation, and soil depth. Consequently, the statistical characteristics of soil depth were analyzed, and the correlations between slope angle and soil depth, and between elevation and soil depth were investigated. Moreover, various soil depth prediction models based on slope angle were investigated, and corrected linear and exponential soil depth prediction models were proposed.

• Journal of Korean Tunnelling and Underground Space Association
• /
• v.25 no.6
• /
• pp.541-554
• /
• 2023

The utilization of underground spaces in relation to tunnels and energy/waste storage is on the rise. To ensure the stability of underground spaces, it is crucial to reinforce rock fractures and discontinuities. Discontinuities, such as joints, can weaken the strength of the rock and lead to groundwater inflow into underground spaces. In order to enhance the strength and stability of the area around these discontinuities, rock grouting techniques are employed. However, during rock grouting, it is impossible to visually confirm whether the grouting material is being smoothly injected as intended. Without proper injection, the expected increases in strength, durability, and degree of consolidation may not be achieved. Therefore, it is necessary to predict in advance whether the grouting material is being injected as designed. In this study, we aimed to assess the injection performance based on injection variables such as the water/cement mixture ratio, injection pressure, and injection flow using UDEC (Universal Distinct Element Code) numerical program. Additionally, numerical results were validated by the lab experiment. The results of this study are expected to help optimize variables such as injection material properties, injection time, and pump pressure in the grouting design in the field.

• Journal of Intelligence and Information Systems
• /
• v.24 no.4
• /
• pp.1-32
• /
• 2018

In addition to stakeholders including managers, employees, creditors, and investors of bankrupt companies, corporate defaults have a ripple effect on the local and national economy. Before the Asian financial crisis, the Korean government only analyzed SMEs and tried to improve the forecasting power of a default prediction model, rather than developing various corporate default models. As a result, even large corporations called 'chaebol enterprises' become bankrupt. Even after that, the analysis of past corporate defaults has been focused on specific variables, and when the government restructured immediately after the global financial crisis, they only focused on certain main variables such as 'debt ratio'. A multifaceted study of corporate default prediction models is essential to ensure diverse interests, to avoid situations like the 'Lehman Brothers Case' of the global financial crisis, to avoid total collapse in a single moment. The key variables used in corporate defaults vary over time. This is confirmed by Beaver (1967, 1968) and Altman's (1968) analysis that Deakins'(1972) study shows that the major factors affecting corporate failure have changed. In Grice's (2001) study, the importance of predictive variables was also found through Zmijewski's (1984) and Ohlson's (1980) models. However, the studies that have been carried out in the past use static models. Most of them do not consider the changes that occur in the course of time. Therefore, in order to construct consistent prediction models, it is necessary to compensate the time-dependent bias by means of a time series analysis algorithm reflecting dynamic change. Based on the global financial crisis, which has had a significant impact on Korea, this study is conducted using 10 years of annual corporate data from 2000 to 2009. Data are divided into training data, validation data, and test data respectively, and are divided into 7, 2, and 1 years respectively. In order to construct a consistent bankruptcy model in the flow of time change, we first train a time series deep learning algorithm model using the data before the financial crisis (2000~2006). The parameter tuning of the existing model and the deep learning time series algorithm is conducted with validation data including the financial crisis period (2007~2008). As a result, we construct a model that shows similar pattern to the results of the learning data and shows excellent prediction power. After that, each bankruptcy prediction model is restructured by integrating the learning data and validation data again (2000 ~ 2008), applying the optimal parameters as in the previous validation. Finally, each corporate default prediction model is evaluated and compared using test data (2009) based on the trained models over nine years. Then, the usefulness of the corporate default prediction model based on the deep learning time series algorithm is proved. In addition, by adding the Lasso regression analysis to the existing methods (multiple discriminant analysis, logit model) which select the variables, it is proved that the deep learning time series algorithm model based on the three bundles of variables is useful for robust corporate default prediction. The definition of bankruptcy used is the same as that of Lee (2015). Independent variables include financial information such as financial ratios used in previous studies. Multivariate discriminant analysis, logit model, and Lasso regression model are used to select the optimal variable group. The influence of the Multivariate discriminant analysis model proposed by Altman (1968), the Logit model proposed by Ohlson (1980), the non-time series machine learning algorithms, and the deep learning time series algorithms are compared. In the case of corporate data, there are limitations of 'nonlinear variables', 'multi-collinearity' of variables, and 'lack of data'. While the logit model is nonlinear, the Lasso regression model solves the multi-collinearity problem, and the deep learning time series algorithm using the variable data generation method complements the lack of data. Big Data Technology, a leading technology in the future, is moving from simple human analysis, to automated AI analysis, and finally towards future intertwined AI applications. Although the study of the corporate default prediction model using the time series algorithm is still in its early stages, deep learning algorithm is much faster than regression analysis at corporate default prediction modeling. Also, it is more effective on prediction power. Through the Fourth Industrial Revolution, the current government and other overseas governments are working hard to integrate the system in everyday life of their nation and society. Yet the field of deep learning time series research for the financial industry is still insufficient. This is an initial study on deep learning time series algorithm analysis of corporate defaults. Therefore it is hoped that it will be used as a comparative analysis data for non-specialists who start a study combining financial data and deep learning time series algorithm.