• Journal of Digital Convergence
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• v.19 no.2
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• pp.69-81
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• 2021

Coastal shipping performs a pivotal role as a national transportation network and is highly valuable in terms of enabling more economical transportation at affordable prices than road transportation. In this regard, this study aimed to examine changes in the characteristics and centrality of South Korea's costal shipping sea-route networks by analyzing the centrality of domestic coastal shipping. To this end, social network analysis was used as an analysis technique that enables an analysis on the characteristics of coastal shipping networks. As a result, Jeollanam-do showed the highest degree centrality, ranking first in both the in-degree and the out-degree. Jeollanam-do also exhibited the highest betweenness centrality, and Gangwon-do registered the highest closeness centrality. In terms of hub and authority centrality, Jeollanam-do topped the list, followed by Gyeongsangnam-do and Gangwon-do in order. Lastly, Jeollanam-do ranked highest in the hub index, followed by Incheon, other regions, and Gangwon-do in order. This study is significant for suggesting the cities and provinces that play a key role in coastal shipping each year and their corresponding items. Future studies are recommended to identify the trend of coastal shipping through more detailed research on each port by city and province.

• FLOWER RESEARCH JOURNAL
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• v.26 no.4
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• pp.195-201
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• 2018

The plant morphological and chromosome characteristics of 'Bonanza', 'Coral Candy' and 'Purple Crystal', a formolongi-Asiatic (FA) interspecific hybrid species bred at the National Institute of Horticultural Science, Rural Development Administration (RDA), were investigated in this study. The flowering time of these species were found to have some variation. 'Bonanza' flowers in the middle to late June (medium-late maturing cultivar), 'Coral Candy' in the mid of June (medium maturing cultivar), and 'Purple Crystal' was observed to be in early June (early maturing cultivar). The flowering direction of all three cultivars are upward facing flowers and having a weak fragrance. The height of the plants was recorded in the range between 101.0 cm ('Purple Crystal') to 142.3 cm ('Bonanza'), thus they are able to develop cut flowers with excellent stem elongation. Flower diameters of 'Bonanza' (17.1 cm) and 'Coral Candy' (16.9 cm) were classified to be large sized flowers. On the other hand, 'Purple Crystal' had a narrow flower diameter (12.3 cm) with an outer petal width of more than 4.0 cm. Leaf length was observed for 'Bonanza' (15.7 cm), 'Coral Candy' (19.7 cm), and 'Purple Crystal' (11.1 cm). Chromosome analysis was done using FISH technique. Results revealed that all three cultivars were observed as triploids (2n=3x=36). FISH analysis also showed 5S/45S rDNA of 'Bonanza', 'Coral Candy' and 'Purple Crystal' as 4/11 loci, 4/12 loci, and 4/11 loci, respectively. The results of the FISH analysis are useful as markers to distinguish cultivars, since the patterns of rDNA observed on the remaining chromosomes are significantly different except FISH patterns of chromosome #3.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.21 no.3
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• pp.183-191
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• 2021

Non-intrusive load monitoring is a technology that can be used for predicting and classifying the type of appliances through real-time monitoring of user power consumption, and it has recently got interested as a means of energy-saving. In this paper, we propose a system for classifying appliances from user consumption data by combining GAF(Gramian angular field) technique that can be used for converting one-dimensional data to the two-dimensional matrix with convolutional neural networks. We use REDD(residential energy disaggregation dataset) that is the public appliances power data and confirm the classification accuracy of the GASF(Gramian angular summation field) and GADF(Gramian angular difference field). Simulation results show that both models showed 94% accuracy on appliances with binary-state(on/off) and that GASF showed 93.5% accuracy that is 3% higher than GADF on appliances with multi-state. In later studies, we plan to increase the dataset and optimize the model to improve accuracy and speed.

• Korean Journal of Remote Sensing
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• v.36 no.6_2
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• pp.1615-1627
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• 2020

The purpose of this study is to compare and analyze the performance of KOMPSAT-3 Digital Surface Model (DSM) made in overseas testbed area. To that end, we collected the KOMPSAT-3 in-track stereo image taken in San Francisco, the U.S. The stereo geometry elements (B/H, converse angle, etc.) of the stereo image taken were all found to be in the stable range. By applying precise sensor modeling using Ground Control Point (GCP) and DSM automatic generation technique, DSM with 1 m resolution was produced. Reference materials for evaluation and calibration are ground points with accuracy within 0.01 m from Compass Data Inc., 1 m resolution Elevation 1-DSM produced by Airbus. The precision sensor modeling accuracy of KOMPSAT-3 was within 0.5 m (RMSE) in horizontal and vertical directions. When the difference map was written between the generated DSM and the reference DSM, the mean and standard deviation were 0.61 m and 5.25 m respectively, but in some areas, they showed a large difference of more than 100 m. These areas appeared mainly in closed areas where high-rise buildings were concentrated. If KOMPSAT-3 tri-stereo images are used and various post-processing techniques are developed, it will be possible to produce DSM with more improved quality.

• Structural Engineering and Mechanics
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• v.78 no.1
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• pp.41-52
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• 2021

Inelastic static pushover analysis has been used in the academic-research widely for seismic analysis of structures. Nowadays, the variety pushover analysis methods have been developed, including Modal pushover, Adaptive pushover, and Cyclic pushover, in which some weaknesses of the conventional pushover method have been rectified. In the conventional pushover analysis method, the effects of cumulative growth of cracks are not considered on the reduction of strength and stiffness of RC members that occur during earthquake or cyclic loading. Therefore, the Cyclic Pushover Analysis Method (CPA) has been proposed. This method is a powerful technique for seismic evaluation of regular reinforced concrete buildings in which the first mode of them is dominant. Since the bridges have different structures than buildings, their results cannot necessarily be attributed to bridges, and more research is needed. In this study, a cyclic pushover analysis with four loading protocols (suggested by valid references) by the Opensees software was conducted for seismic evaluation of two regular reinforce concrete bridges. The modeling method was validated with the comparison of the analytical and experimental results under both cyclic and dynamic loading. The failure mode of the piers was considered in two-mode of flexural failure and also a flexural-shear failure. Along with the cyclic analysis, conventional analysis has been studied. Also, the nonlinear incremental dynamic analysis (IDA) method has been used to examine and compare the results of pushover analyses. The time history of 20 far-field earthquake records was used to conduct IDA. After analysis, the base shear vs. displacement in the middle of the deck was drawn. The obtained results show that the cyclic pushover analysis method is able to evaluate an accurate seismic behavior of the reinforced concrete piers of the bridges. Based on the results, the cyclic pushover has proper convergence with IDA. Its accuracy was much higher than the conventional pushover, in which the bridge piers failed in flexural-shear mode. But, in the flexural failure mode, the results of each two pushover methods were close approximately. Besides, the cyclic pushover method with ACI loading protocol, and ATC-24 loading protocol, can provided more accurate results for evaluating the seismic investigation of the bridges, specially if the bridge piers are failed in flexural-shear failure mode.

• The Journal of the Convergence on Culture Technology
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• v.7 no.3
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• pp.577-582
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• 2021

Recently, with the development of AR, VR, and smart device technologies, the demand for services based on non-face-to-face environments is also increasing in the fitness industry. The non-face-to-face online home training service has the advantage of not being limited by time and place compared to the existing offline service. However, there are disadvantages including the absence of exercise equipment, difficulty in measuring the amount of exercise and chekcing whether the user maintains an accurate exercise posture or not. In this study, we develop a standard exercise program that can compensate for these shortcomings and propose a new non-face-to-face home training application by using a deep learning-based body posture estimation image processing algorithm. This application allows the user to directly watch and follow the trainer of the standard exercise program video, correct the user's own posture, and perform an accurate exercise. Furthermore, if the results of this study are customized according to their purpose, it will be possible to apply them to performances, films, club activities, and conferences

• Journal of Digital Convergence
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• v.20 no.4
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• pp.169-184
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• 2022

The purpose of this study is to give a help organizations facing various crises establish effective crisis preparedness plans by confirming the effect of an organization's crisis management system on crisis preparedness, and by confirming the multiple mediating effects of crisis monitoring and learning from failure. The survey for the empirical study was conducted targeting 121 executives, directors, mangers and mid-level employees of the MBA program of the P National University. Confirmatory factor analysis, reliability analysis, and regression analysis were performed using SPSS 25 and Amos 25, and mediating effect analysis was performed using the boot-strapping technique using process macro. As a result of the study, it was found that the crisis management system had a positive (+) effect on crisis preparedness, and learning from failure and crisis monitoring multi-mediate between the crisis management system and crisis preparedness. Through the research results, it was confirmed that there was a significant effect of learning from failure and crisis monitoring that had an effect on crisis preparedness. As an implication, a crisis preparedness plan suitable for the organizational situation was presented, and the limitations of the study and future research directions were presented.

• The Journal of the Convergence on Culture Technology
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• v.8 no.1
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• pp.19-29
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• 2022

This study was conducted with the aim of verifying the effects of restaurant video taping and job communication drawing board production activities on cooking job skills of high school students with intellectual disabilities. The study participants consisted of three students with intellectual disabilities enrolled in the high school course of a special school, and the experimental environment consisted of a kitchen in the restaurant and a classroom in the special school. For the research design, the technique of multiple probe design across subjects according to a single subject research was used. The intervention program consisting of independent variables was applied as a linkage procedure in which study participants videotaped the kitchen's environmental facilities, tools, materials, and staff perform cooking job skills and then taped data from the classroom scene on a job communication drawing board. Cooking job skills consisting of dependent variables are defined as the performance of research participants cooking gimbap directly in the kitchen of the restaurant. As a result of the study, it was found that participants effectively acquired, maintained, and generalized cooking job skills through intervention programs.

• Journal of Korean Academy of Nursing
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• v.51 no.6
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• pp.703-719
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• 2021

Purpose: We aimed to identify collaborative disaster governance through the demand and supply analysis of resources recognized by nurses during the COVID-19 pandemic. Methods: We used a descriptive study design with an online survey technique for data collection. The survey questions were developed based on focus group interviews with nurses responding to COVID-19 and expert validity testing. A 42-question online survey focusing on disaster governance was sent to nurses working in COVID-19 designated hospitals, public health offices, and schools. A total of 630 nurses participated in the survey. Demand and supply analysis was used to identify the specific components of disaster governance during a pandemic situation and analyze priority areas in disaster governance, as reported by nurses. Results: Demand and supply analysis showed that supplies procurement, cooperation, education, and environment factors clustered in the high demand and supply quadrant while labor condition, advocacy, emotional support, and workload adjustment factors clustered in the high demand but low supply quadrant, indicating a strong need in those areas of disaster governance among nurses. The nurses practicing at the public health offices and schools showed major components of disaster governance plotted in the second quadrant, indicating weak collaborative disaster governance. Conclusion: These findings show that there is an unbalanced distribution among nurses, resulting in major challenges in collaborative disaster governance during COVID-19. In the future and current pandemic, collaborative disaster governance, through improved distribution, will be useful for helping nurses to access more required resources and achieve effective pandemic response.

• Journal of Industrial Convergence
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• v.20 no.6
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• pp.27-35
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• 2022

The purpose of this study is to analyze the metaverse-related issues in the news big data from an educational perspective, explore their characteristics, and provide implications for the educational applicability of the metaverse and future education. To this end, 41,366 cases of metaverse-related data searched on portal sites were collected, and weight values of all extracted keywords were calculated and ranked using TF-IDF, a representative term weight model, and then word cloud visualization analysis was performed. In addition, major topics were analyzed using topic modeling(LDA), a sophisticated probability-based text mining technique. As a result of the study, topics such as platform industry, future talent, and extension in technology were derived as core issues of the metaverse from an educational perspective. In addition, as a result of performing secondary data analysis under three key themes of technology, job, and education, it was found that metaverse has issues related to education platform innovation, future job innovation, and future competency innovation in future education. This study is meaningful in that it analyzes a vast amount of news big data in stages to draw issues from an education perspective and provide implications for future education.