• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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• v.27 no.1
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• pp.33-47
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• 2022

In this study, distribution of submarine sand ridges in the coastal waters of Korea was surveyed using multibeam echo sounder data, and the topographic characteristics of each region were identified. For this purpose, the DEM (Digital Elevation Model) data was generated using depth data obtained from the Yellow Sea and the South Sea by Korea Hydrographic and Oceanographic Agency, and then applied the TPI (Topographic Position Index) technique to precisely extract the boundary of the sand ridges. As a result, a total of 200 sand ridges distributed in the coastal waters were identified, and the characteristics of each region of the sedimentary sediments were analyzed by performing statistical analysis on the scale (width, length, perimeter, area, height) and shape (width/length ratio, height/width ratio, linear·branch type, exposure·non-exposure type). The results of this study are expected to be used not only for coastal navigational safety, but also for marine naming support, marine aggregate resource identification, and fisheries resource management.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.7 no.7
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• pp.267-278
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• 2017

The aim of this paper was to develop a scale for measuring gender identity among sports participants (114 male, 193 female). Gender similarities and latent mean analysis was used to validate the gender identity measurement method. Data processing was carried out by way of frequency analysis, exploratory and confirmatory factor analysis, reliability, correlation, normal distribution of questions, and latent mean analysis using SPSS 18.0 and AMOS 18.0. The results of this study were as follows: First, the equivalence had revealed the configurable, metric, and scalar invariance of the scale that can be used in multi-groups in the same way. Second, women had a more open inclination than men when it came to participating in sports activities (p<.001). Third, women participating in sports activities tended to be more conservative than men (p<.001). Fourth, women who participated in sports activities showed a higher subjective tendency than men (p<.001). Fifth, there was no statistical difference in the outward tendency when participating in sports activities (p<.05). The results of this study suggest that gender identity among sports participants is not influenced by the changing times and the advancement of women in society.

• The Journal of Bigdata
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• v.6 no.2
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• pp.139-149
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• 2021

Ddareungi, a public bicycle service in Seoul, establishes itself as a means of daily transportation for citizens in Seoul. We speculated that the pattern of using Ddareungi may have changed since COVID-19. This study explores changes in using Ddareungi after COVID-19 with descriptive statistical analysis and network analysis. The analysis results are summarized as follows. The average traveling distance and average traveling speed have decreased over the entire time in a day since COVID-19. The round trip rate has increased at dawn and morning and has decreased in the evening and night. The average weighted degree and average clustering coefficient have decreased, and the modularity has increased. The clusters, located north of the Han River in Seoul, had a similar geographic distribution before and after COVID-19. However, the clusters, located south of the Han River, had different geographic distributions after COVID-19. Traveling routes added to the top 5 traffic rankings after COVID-19 had an average traveling distance of fewer than 1,000 meters. We expect that the results of this study will help improve the public bicycle service in Seoul.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.30 no.5B
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• pp.487-495
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• 2010

Soil moisture is a crucial factor in hydrological system which influences runoff, energy balance, evaporation, and atmosphere. United States National Aeronautic and Space Administration (NASA) and Department of Agriculture (USDA) have established Soil Moisture Experiment (SMEX) since 2002 for the global observations. SMEX provides useful data for the hydrological science including soil moisture and hydrometeorological variables. The purpose of this study is to investigate the relationship between remotely sensed soil moisture data from aircraft and satellite and ground based experiment. C-band of Polarimetric Scanning Radiometer (PSR) that observed the brightness temperature provides soil moisture data using a retrieval algorithm. It was compared with the In-situ data for 2-30 cm depth at four sites. The most significant depth is 2-10 cm from the correlation analysis. Most of the sites, two data are similar to the mean of data at 10 cm and the median at 7 cm and 10 cm at the 10% significant level using the Rank Sum test and t-test. In general, soil moisture data using the C-band of the PSR was established to fit the Normal, Log-normal and Gumbel distribution. Soil moisture data using the aircraft and satellites will be used in hydrological science as fundamental data. Especially, the C-band of PSR will be used to prove soil moisture at 7-10 cm depths.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2022.06a
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• pp.383-384
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• 2022

Following the development of technologies such as digital twin, IoT, and AI after the 4th industrial revolution, decision-making problems are being solved based on high-dimensional data analysis. This has recently been applied to the port logistics sector, and a number of studies on big data analysis, deep learning predictions, and simulations have been conducted on container terminals to improve port productivity. These high-dimensional data analysis techniques generally require a large number of data. However, the global port environment has changed due to the COVID-19 pandemic in 2020. It is not appropriate to apply data before the COVID-19 outbreak to the current port environment, and the data after the outbreak was not sufficiently collected to apply it to data analysis such as deep learning. Therefore, this study intends to present a port data augmentation method for data analysis as one of these problem-solving methods. To this end, we generate the container stowage situation of the yard through a generative adversarial neural network model in terms of container terminal operation, and verify similarity through statistical distribution verification between real and augmented data.

• Journal of Korea Water Resources Association
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• v.56 no.8
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• pp.471-484
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• 2023

Deep learning models based on generative adversarial neural networks are specialized in generating new information based on learned information. The deep generative models (DGMR) model developed by Google DeepMind is an generative adversarial neural network model that generates predictive radar images by learning complex patterns and relationships in large-scale radar image data. In this study, the DGMR model was trained using radar rainfall observation data from the Ministry of Environment, and rainfall prediction was performed using an generative adversarial neural network for a heavy rainfall case in August 2021, and the accuracy was compared with existing prediction techniques. The DGMR generally resembled the observed rainfall in terms of rainfall distribution in the first 60 minutes, but tended to predict a continuous development of rainfall in cases where strong rainfall occurred over the entire area. Statistical evaluation also showed that the DGMR method is an effective rainfall prediction method compared to other methods, with a critical success index of 0.57 to 0.79 and a mean absolute error of 0.57 to 1.36 mm in 1 hour advance prediction. However, the lack of diversity in the generated results sometimes reduces the prediction accuracy, so it is necessary to improve the diversity and to supplement it with rainfall data predicted by a physics-based numerical forecast model to improve the accuracy of the forecast for more than 2 hours in advance.

• The Journal of Korean Medicine Ophthalmology and Otolaryngology and Dermatology
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• v.36 no.4
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• pp.1-18
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• 2023

Objectives : This study retrospectively analyzed the medical records of patients admitted to Korean medicine ophthalmology, otolaryngology and dermatology department of Daejeon Korean medicine hospital from March 2018 to February 2023 to analyze the characteristics of patients receiving inpatient treatment. Methods : We retrospectively analyzed inpatients who admitted to ophthalmology & otolaryngology & dermatology clinic of Daejeon Korean medicine hospital from March 1st, 2018 to February 28th, 2023, according to gender, age, year, season, detailed subdivision. The statistical analysis performed using IBM SPSS 29.0 for Windows. Results : 1. Examining the gender distribution of the patient group, there were 367 female patients, accounting for 71.7% of the total patients, and 145 male patients, accounting for 28.3% of the total patients. 2. When analyzing inpatients by subdivision, otology accounted for more than half of the total number of inpatients, and the combined number of otology and dermatology accounted for more than 80% of the total. 3. As a result of analyzing inpatients by frequent disease, Sudden hearing loss was a significantly higher number of patients, accounting for 22.7% of all inpatients. Conclusions : It was found that the proportion of patients with otologic diseases was very prominent. It is thought that further research is needed to see if the trend of increasing demand for otologic diseases continues.

• Journal of Venture Innovation
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• v.6 no.3
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• pp.131-148
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• 2023

This study analyzed the effect of marketing ability of SMEs using online export marketing on market performance. Small and medium-sized enterprises (SMEs) are making efforts to expand their markets from the domestic market to the overseas market and increase sales. We studied the factors that can produce results in the fiercely competitive overseas market. A total of 400 export SMEs were surveyed, and 159 companies directly participating in online export marketing were selected as final targets. The survey was analyzed using SMART PLS 4.0 and SPSS 26.0 statistical programs, and research hypotheses were verified. The results of the study are as follows. First, it was found that the marketing ability of SMEs had a positive (+) effect on online export marketing. Second, it was confirmed that online export marketing had a significant positive (+) effect on market performance through its mediating role. In addition, the intensity of competition in the export market was found to have a moderating effect in online export marketing. The implications of this study are as follows. The theoretical basis was established that the marketing capabilities (product development capability, distribution capability, pricing capability, public relations capability) of exporting SMEs have a positive effect on overseas market performance through online export marketing. In the market, the use of online export marketing by SMEs can provide implications in that it can be an important means for overseas market development and performance. As a result, it is necessary to actively utilize online export marketing for SMEs to enter overseas markets and achieve results.

• Journal of Internet Computing and Services
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• v.24 no.5
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• pp.17-27
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• 2023

Today, as AI (Artificial Intelligence) technology develops and its practicality increases, it is widely used in various application fields in real life. At this time, the AI model is basically learned based on various statistical properties of the learning data and then distributed to the system, but unexpected changes in the data in a rapidly changing data situation cause a decrease in the model's performance. In particular, as it becomes important to find drift signals of deployed models in order to respond to new and unknown attacks that are constantly created in the security field, the need for lifecycle management of the entire model is gradually emerging. In general, it can be detected through performance changes in the model's accuracy and error rate (loss), but there are limitations in the usage environment in that an actual label for the model prediction result is required, and the detection of the point where the actual drift occurs is uncertain. there is. This is because the model's error rate is greatly influenced by various external environmental factors, model selection and parameter settings, and new input data, so it is necessary to precisely determine when actual drift in the data occurs based only on the corresponding value. There are limits to this. Therefore, this paper proposes a method to detect when actual drift occurs through an Anomaly analysis technique based on XAI (eXplainable Artificial Intelligence). As a result of testing a classification model that detects DGA (Domain Generation Algorithm), anomaly scores were extracted through the SHAP(Shapley Additive exPlanations) Value of the data after distribution, and as a result, it was confirmed that efficient drift point detection was possible.

• Journal of Internet of Things and Convergence
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• v.10 no.2
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• pp.137-148
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• 2024

The purpose of this study is to determine how the use of retailtech technology affects consumers' purchase intention. Furthermore, this study aims to investigate the mediating effects of technology usefulness and ease of use on this influence relationship and whether experiential marketing moderates consumers' purchase intention. The survey was conducted from August 1, 2023 to September 30, 2023, and a total of 257 people participated in the study. For statistical analysis, hierarchical regression analysis, three-stage mediation regression analysis, and hierarchical three-stage controlled regression analysis were conducted to test the hypothesis. The results of the study are as follows. First, it was confirmed that big data-AI utilization, mobile-SNS utilization, live commerce utilization, and IoT utilization affect purchase intention in retail technology utilization. Second, technology usefulness has a mediating effect on IoT utilization, mobile-SNS utilization, and big data-AI utilization. Third, perceived ease of use of technology mediated the effects of IoT utilization, mobile-SNS utilization, live-commerce utilization, and big data-AI utilization. Fourth, escapist experience has a moderating effect on mobile SNS utilization and live commerce utilization. Fifth, esthetic experience has a moderating effect on mobile-SNS utilization and big data-AI utilization. Through this study, we hope that the domestic distribution industry will contribute to national competitiveness by securing the competitive advantage of companies by utilizing new technologies in entering the global market.