• Journal of Korean Society of Coastal and Ocean Engineers
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• v.33 no.6
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• pp.217-225
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• 2021

In this study, wave spectrum data were calculated using the water surface elevation data observed at 5Hz intervals from the HeMOSU-2 meteorological tower installed on the west coast of Korea, and wave parameters were estimated using wave spectrum data. For all significant wave height ranges, the peak enhancement parameter (γ_opt) of the JONSWAP spectrum and the scale parameter (α) and shape parameter (β) of the modify BM spectrum were estimated based on the observed spectrum, and the distribution of each parameter was confirmed. As a result of the analysis, the peak enhancement parameter (γ_opt) of the JONSWAP spectrum was calculated to be 1.27, which is very low compared to the previously proposed 3.3. And in the range of all significant wave heights, the distribution of the peak enhancement parameter (γ_opt) was shown as a combined distribution of probability mass function (PMF) and probability density function (PDF). In addition, the scale parameter (α) and shape parameter (β) of the modify BM spectrum were estimated to be [0.245, -1.278], which are lower than the existing [0.300, -1.098], and the result of the linear correlation analysis between the two parameters was β = -3.86α.

• Journal of the Korean Society for information Management
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• v.38 no.4
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• pp.1-23
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• 2021

The purpose of this study is to analyze the effects of the bestseller ranks on the book circulations in public libraries. To achieve this goal, the weekly data sets of 179 books' library circulation and bestseller list from January 1, 2018 to December 29, 2019 were constructed based on the data collected from BigData MarketC and YES24. Three methods for analyzing panel data including linear regression, fixed-effect, and random effect models were compared, and it turned out that fixed-effect model was better than other methods. The results show that the average ranks of bestsellers were associated with their public library circulations visually. Also, the analysis of fixed-effect model showed that the single rank decline of a book on the bestseller list decreases its average circulation of 0.108 while the size of effect varied depending on subject of books. The study empirically demonstrated the impact of a bestseller list on people's book circulation behavior, suggesting that public libraries need to reference sociocultural context as well as bestseller book lists to predict library user needs and to formulate collection development policy.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.20 no.6
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• pp.84-99
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• 2021

As the micro-mobility market grows, the demand for route guidance, that includes uphill information as well, is increasing. Since the climbing angle depends on the electric motor uesed, it is necessary to establish an uphill road DB according to the threshold standard. Although road alignment information is a very important element in the basic information of the roads, there is no information currently on the longitudinal slope in the road digital map. The High Definition(HD) map which is being built as a preparation for the era of autonomous vehicles has the altitude value, unlike the existing standard node link system. However, the HD map is very insufficient because it has the altitude value only for some sections of the road network. This paper, hence, intends to propose a method to generate the road longitudinal slope using currently available data. We developed a method of computing the longitudinal slope by combining the digital elevation model and the standard link system. After creating an altitude at the road link point divided by 4m based on the Seoul road network, we calculated individual slope per unit distance of the road. After designating a representative slope for each road link, we have extracted the very steep road that cannot be climbed with personal mobility and the slippery roads that cannot be used during heavy snowfall. We additionally described errors in the altitude values due to surrounding terrain and the issues related to the slope calculation method. In the future, we expect that the road longitudinal slope information will be used as basic data that can be used for various convergence analyses.

• Journal of the Korea Computer Graphics Society
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• v.27 no.5
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• pp.1-11
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• 2021

The purpose of our research is to efficiently deform a 3D models which is composed of a triangular mesh and a skeleton. We designed a novel inverse kinematics (IK) solver that calculates the updated positions of mesh vertices with fewer computing operations. Through our user interface, one or more markers are selected on the surface of the model and their target positions are set, then the system updates the positions of surface vertices to construct a deformed model. The IK solving process for updating vertex positions includes many computations for obtaining transformations of the markers, their affecting joints, and their parent joints. Many of these computations are often redundant. We precompute those redundant terms in advance so that the 3-nested loop computation structure was improved to a 2-nested loop structure, and thus the computation time for a deformation is greatly reduced. This novel IK solver can be adopted for efficient performance in various research fields, such as handling 3D models implemented by LBS method, or object tracking without any markers.

• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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• v.27 no.2
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• pp.49-70
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• 2022

Sea Surface Temperature (SST), one of the ocean features, has a significant impact on climate, marine ecosystem and human activities. Therefore, SST prediction has been always an important issue. Recently, deep learning has drawn much attentions, since it can predict SST by training past SST patterns. Compared to the numerical simulations, deep learning model is highly efficient, since it can estimate nonlinear relationships between input data. With the recent development of Graphics Processing Unit (GPU) in computer, large amounts of data can be calculated repeatedly and rapidly. In this study, Short-term SST will be predicted through Convolutional Neural Network (CNN)-based U-Net that can handle spatiotemporal data concurrently and overcome the drawbacks of previously existing deep learning-based models. The SST prediction performance depends on the seasonal and interannual SST variabilities around the southern coast of Korea. The predicted SST has a wide range of variance during spring and summer, while it has small range of variance during fall and winter. A wide range of variance also has a significant correlation with the change of the Pacific Decadal Oscillation (PDO) index. These results are found to be affected by the intensity of the seasonal and PDO-related interannual SST fronts and their intensity variations along the southern Korean seas. This study implies that the SST prediction performance using the developed deep learning model can be significantly varied by seasonal and interannual variabilities in SST.

• The Journal of the Korea Contents Association
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• v.22 no.1
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• pp.620-628
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• 2022

The purpose of this study is to confirm the degree of improvement in performance confidence and executive ability after conducting field adaptation education to dental hygiene students who start their first field practice. Thirty dental hygiene students were evaluated with performance confidence, indirect and direct evaluation of practical skill before and after the field adaptation education was conducted for 15 hours. Also field practice satisfaction was investigated after field practice. A paired t-test was conducted to compare performance confidence, indirect executive ability, and direct practical ability before and after education. Pearson's correlation was performed on the correlation between field adaptation education and field practice satisfaction. Linear regression analysis was performed to identify the influencing factors of field practice satisfaction. As a results, performance confidence, indirect and direct practical skills of after field adaptation program were increased than before that(p<0.05). The correlation between field adaptation education and field practice satisfaction showed that "education satisfaction" among the field adaptation education sub-regions correlated with "education content" and "support of field practice" among the field practice satisfaction sub-regions(p<0.05). Therefore, it is necessary to develop and management various adaptation education in the future as it increases the adaptability of the first field practice and increases the satisfaction of field practice.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.40 no.2
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• pp.119-133
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• 2022

Due to the improvement of surveying, mapping and communication techniques, various apps for road direction guides and vehicle navigations have been developed. Although such a development has impacted on walking and driving, there is a limit to improving the daily convenience of the socially impaired people. This is mainly due to the fact that the software have been developed for normal pedestrians and drivers. Therefore, visually impaired people still have problems with the confusion of direction and/or non-provision of risk factors in walking. This study aimed to propose a scheme which constructs data for mobility-impaired or traffic-impaired people based on various geospatial information. The factors and components related to walking for the visually impaired are selected by geospatial data and a walking route guidance network that can be applied to a commercial software. As a result, it was confirmed that road direction guidance would be possible if additional contents, such as braille blocks (dotted/linear), sound signals, bus stops, and bollards are secured. In addition, an initial version of the application software was implemented based on the suggested data model and its usefulness was evaluated to a visually impaired person. To advance the stability of the service in walking for the visually impaired people, various geospatial data obtained by multiple institutes are necessary to be combined, and various sensors and voice technologies are required to be connected and utilized through ICT (Information and Communications Technologies) technology in near future.

• Korean small business review
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• v.42 no.1
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• pp.135-165
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• 2020

This study aimed to examine relationships between founders' entrepreneurial leadership, team learning behavior, team boundary spanning, and perceived performance in early-stage startups. The following results were recorded: (i) the indirect effects of entrepreneurial leadership on perceived performance via team learning behavior were statistically significant (β=.309, p<.05). (ii) relationships between team learning behavior and perceived performance were strengthened by team boundary spanning behavior (β=.259, p<.05). In this study, three practical implications are provided as follows: (i) startups need to seek team learning readiness and external learning stimulus to facilitate generative and transformative team learning; (ii) accelerators need to develop an entrepreneurial leadership program for founders; and (iii) startups need to explore external information by interacting with investors, R&D institutions, and other startups to strengthen the impact of team learning behavior on performance. Furthermore, two directions for future research are suggested as follows: (i) future researchers need to test causal relationships between entrepreneurial leadership and team learning behavior based on a newly designed time-series measurement plan; (ii) the actual effects of entrepreneurial leadership, team learning behavior and team boundary spanning on financial performance need to be tested two or three years later when the financial performance of early-stage startups usually becomes evident.

• KIPS Transactions on Computer and Communication Systems
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• v.12 no.2
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• pp.85-92
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• 2023

Respiratory infections such as COVID-19 mainly occur within enclosed spaces. The presence or absence of abnormal symptoms of respiratory infectious diseases is judged through initial symptoms such as fever, cough, sneezing and difficulty breathing, and constant monitoring of these early symptoms is required. In this paper, image matching correction was performed for the RGB camera module and the thermal imaging camera module, and the temperature of the thermal imaging camera module for the measurement environment was calibrated using a blackbody. To detection the target recommended by the standard, a deep learning-based object recognition algorithm and the inner canthus recognition model were developed, and the model accuracy was derived by applying a dataset of 100 experimenters. Also, the error according to the measured distance was corrected through the object distance measurement using the Lidar module and the linear regression correction module. To measure the performance of the proposed model, an experimental environment consisting of a motor stage, an infrared thermography temperature screening system and a blackbody was established, and the error accuracy within 0.28℃ was shown as a result of temperature measurement according to a variable distance between 1m and 3.5 m.

• Journal of the Korean Association of Geographic Information Studies
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• v.25 no.3
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• pp.74-99
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• 2022

Surface ozone is produced by photochemical reactions of nitrogen oxides(NOx) and volatile organic compounds(VOCs) emitted from vehicles and industrial sites, adversely affecting vegetation and the human body. In South Korea, ozone is monitored in real-time at stations(i.e., point measurements), but it is difficult to monitor and analyze its continuous spatial distribution. In this study, surface ozone concentrations were interpolated to have a spatial resolution of 1.5km every hour using the stacking ensemble technique, followed by a 5-fold cross-validation. Base models for the stacking ensemble were cokriging, multi-linear regression(MLR), random forest(RF), and support vector regression(SVR), while MLR was used as the meta model, having all base model results as additional input variables. The results showed that the stacking ensemble model yielded the better performance than the individual base models, resulting in an averaged R of 0.76 and RMSE of 0.0065ppm during the study period of 2020. The surface ozone concentration distribution generated by the stacking ensemble model had a wider range with a spatial pattern similar with terrain and urbanization variables, compared to those by the base models. Not only should the proposed model be capable of producing the hourly spatial distribution of ozone, but it should also be highly applicable for calculating the daily maximum 8-hour ozone concentrations.