• Journal of Korea Water Resources Association
• /
• v.54 no.spc1
• /
• pp.1023-1035
• /
• 2021

The electricity cost of a desalination facility was also predicted and reviewed, which allowed the proposed model to be incorporated into the future design of such facilities. Input data from 2003 to 2014 of the Korea Hydrographic and Oceanographic Agency (KHOA) were used, and the structure of the model was determined using the trial and error method to analyze as well as hyperparameters such as salinity and seawater temperature. The future seawater quality was estimated by optimizing the prediction model based on machine learning. Results indicated that the seawater temperature would be similar to the existing pattern, and salinity showed a gradual decrease in the maximum value from the past measurement data. Therefore, it was reviewed that the electricity cost for seawater desalination decreased by approximately 0.80% and a process configuration was determined to be necessary. This study aimed at establishing a machine-learning-based prediction model to predict future water quality changes, reviewed the impact on the scale of seawater desalination facilities, and suggested alternatives.

• Smart Media Journal
• /
• v.12 no.3
• /
• pp.120-128
• /
• 2023

There are various ICT technologies continuously being developed to reduce damage by industrial accidents. And research is being conducted to minimize damage in case of industrial accidents by utilizing sensors, IoT, big data, machine learning and artificial intelligence. In this paper, we propose a design method for a smart device capable of multilateral communication between devices and smart repeater in the communication shaded Areas such as closed areas of industrial sites, mountains, oceans, and coal mines. The proposed device collects worker's information such as worker location and movement speed, and environmental information such as terrain, wind direction, temperature, and humidity, and secures a safe distance between workers to warn in case of a dangerous situation and is designed to be attached to a helmet. For this, we proposed functional requirements for smart devices and design methods for implementing each requirement using sensors and modules in smart device. And we derived evaluation items for performance evaluation of the smart device and proposed an evaluation environment for performance evaluation in mountainous area.

• Journal of Korea Port Economic Association
• /
• v.39 no.4
• /
• pp.1-21
• /
• 2023

This study analyzed workers' residence and home-based work(HBW) trip by utilizing data from mobile carrier base stations of Gwangyang Port and terminal workers. In the past, research on port-related traffic or trip patterns mainly focused on cargo-based movement patterns for estimating cargo volume and port facilities, but this study analyzed trip patterns for workers in Gwangyang Port ports and related industries. As a result of the analysis, the average number of regular workers in the port hinterland Gwangyang Port was 1,295 per month, and the residence of workers was analyzed in Gwangyang City (66.1%)>Suncheon City (26.6%)>Yeosu City (3.1%). The average number of temporary workers in the hinterland was 2,645 per month, and Gwangyang City (45.8%)>Suncheon City (20.1%)>Yeosu City (5.7%). Next, the average number of regular workers at Gwangyang Port terminals was 753 per month, and Gwangyang City (66.1%)>Suncheon City (28.9%)>Yeosu City (3.3%) was analyzed. The average number of temporary workers at Gwangyang Port terminals was 1,893 per month, and Gwangyang City (50.8%)>Suncheon City (19.7%)>Yeosu City (9.8%). This study is expected to calculate the number of workers based on individual traffic using actual mobile carrier data to estimate the actual number of workers if the workplace address and actual work place are different, such as in port-related industries. This study is the first to be conducted on workers at Gwangyang Port. It is expected to be used as basic data for settlement conditions and urban planning, as well as transportation policies for port workers, by identifying the population coming from areas other than Gwangyang, where Gwangyang Port is located.

• Journal of Ocean Engineering and Technology
• /
• v.33 no.6
• /
• pp.590-596
• /
• 2019

Numerous deaths and substantial property damage have occurred recently due to frequent disasters of the highest intensity according to the abnormal climate, which is caused by various problems, such as global warming, all over the world. Such large-scale disasters have become an international issue and have made people aware of the disasters so they can implement disaster-prevention measures. Extensive information on disaster prevention actively has been announced publicly to support the natural disaster reduction measures throughout the world. In Japan, diverse developmental studies on disaster prevention systems, which support hazard map development and flood control activity, have been conducted vigorously to estimate external forces according to design frequencies as well as expected maximum frequencies from a variety of areas, such as rivers, coasts, and ports based on broad disaster prevention data obtained from several huge disasters. However, the current reduction measures alone are not sufficiently effective due to the change of the paradigms of the current disasters. Therefore, in order to obtain the synergy effect of reduction measures, a study of the establishment of an integrated system is required to improve the various disaster prevention technologies and the current disaster prevention system. In order to develop a similar typhoon search system and establish a disaster prevention infrastructure, in this study, techniques will be developed that can be used to forecast typhoons before they strike by using artificial intelligence (AI) technology and offer primary disaster prevention information according to the direction of the typhoon. The main function of this model is to predict the most similar typhoon among the existing typhoons by utilizing the major typhoon information, such as course, central pressure, and speed, before the typhoon directly impacts South Korea. This model is equipped with a combination of AI and DNN forecasts of typhoons that change from moment to moment in order to efficiently forecast a current typhoon based on similar typhoons in the past. Thus, the result of a similar typhoon search showed that the quality of prediction was higher with the grid size of one degree rather than two degrees in latitude and longitude.

• Journal of Korea Water Resources Association
• /
• v.54 no.6
• /
• pp.433-442
• /
• 2021

In order to examine the characteristics of tidal wave from the estuary to upsteam of tidal river, tidal asymmetry was identified based on analysis of the harmonic constants of M2 and M4 tidal constituents in the domestic western coastal regions. As shallow water tide is greatly developed in the estuary, flood dominance in Han River and Keum River, and ebb dominance in Youngsan River are developed. These tidal asymmetries can be reconfirmed by analyzing the tidal current data. Unlike having reciprocating tidal current patterns in Keum and Youngsan estuaries, rotaing tidal current pattern is shown in the Han River estuary due to the complex topography and waterways around Ganghwa Island area. However, when residual current is removed, flood dominance is shown in consistency with the tide data. The tidal asymmetry in the estuary tends to intensify with the growth in shallow water tide as the tidal wave propagates to upstream of tidal river. Energy dissipation, in shallow Han River and Keum River classified as SD estuaries, is very large regarding bottom friction characteristics. On the other hand, the deep Youngsan River, classified as a WD estuary, shows less energy dissipation.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
• /
• 2022.06a
• /
• pp.391-393
• /
• 2022

In recent years, technologies forecasting demand based on deep learning and big data have accelerated the smartification of the field of e-commerce, logistics and distribution areas. In particular, ports, which are the center of global transportation networks and modern intelligent logistics, are rapidly responding to changes in the global economy and port environment caused by the 4th industrial revolution. Port traffic forecasting will have an important impact in various fields such as new port construction, port expansion, and terminal operation. Therefore, the purpose of this study is to compare the time series analysis and deep learning analysis, which are often used for port traffic prediction, and to derive a prediction model suitable for the future container prediction of Busan Port. In addition, external variables related to trade volume changes were selected as correlations and applied to the multivariate deep learning prediction model. As a result, it was found that the LSTM error was low in the single-variable prediction model using only Busan Port container freight volume, and the LSTM error was also low in the multivariate prediction model using external variables.

• Spatial Information Research
• /
• v.21 no.4
• /
• pp.71-81
• /
• 2013

Due to explosively increasing utilization in spatial information and a rapid development in geospatial technology related to national territorial and housing, there are increasing demands for converging spatial information on not only urban planning and real estate data but also newly generated data from smart phone, GPS to achieve comparative advantage of national territory. In this paper, we prospect the utilization of Converged Spatial Information(CSI) to future national territorial planning for the purpose of enhancing territorial competitiveness. For this purpose, considering the Korea Land and Housing corporation(LH) takes charge most of government's land and housing development projects, CSI usage of this company's 6 future business domains until 2029 were used as a case study. Also, 7 CSIs derived from literature review were surveyed to find the degree of CSI utilization in the national territorial future. In the analysis result, it was found that 3D data and mobile data among others have higher degree of utilization, and urban and regional development is the most highly utilizable domain for CSIs. After all, to revitalize the use of CSI in national territorial future, it is required to do a balanced construction of territorial use spatial information about marine use, coastal use, underground space besides land use.

• KSCE Journal of Civil and Environmental Engineering Research
• /
• v.42 no.5
• /
• pp.639-650
• /
• 2022

In areas where large-scale sediment transport occurs, it is important to apply appropriate countermeasure method because the phenomenon tends to accelerate by time duration. Among the various countermeasure methods applied so far, beach nourishment needs to be reviewed as an erosion prevention measure because the erosion pattern is mitigated and environmentally friendly depending on the particle size. In the case of beach nourishment. a detailed review is required to determine the size, range, etc., of an appropriate particle diameter. In this study, we investigated the characteristics of the related topographic change using the change in the particle size of nourishment materials, the application of partial area, and the condition under the coexistence of waves and wind as variables because those factors are hard to be analyzed and interpreted within results and limitation of that the existing numerical models are not able to calculate and result out so that it is required that phenomenon or efforts are reviewed at the same time through physical model experiments, field monitoring and etc. So we attempt to reproduce the tendency of beach erosion and deposition and predict possible phenomena in the future using machine learning techniques for phenomena that it is not able to be interpreted by numerical models. we used the hydraulic experiment results for the training data, and the accuracy of the prediction results according to the change in the training method was simultaneously analyzed. As a result of the study it was found that topographic changes using machine learning tended to be similar to those of previous studies in short-term predictions, but we also found differences in the formation of scour and sandbars.

• Journal of the Korean Association of Geographic Information Studies
• /
• v.16 no.1
• /
• pp.15-25
• /
• 2013

The RIMGIS(River Information Management GIS) has been developed since 2000 for public service and practical applications of related works after the standardization of national river data such as the river facility register report, river survey map, attached map, and etc. The RIMGIS has been improved in order to respond proactively to change in the information environment. Recently, Smart River-based river information services and related data have become so large as to be overwhelming, making necessary improvements in managing big data. In this study a plan was suggested both to respond to these changes in the information environment and to provide a future Smart River-based river information service by understanding the current state of RIMGIS, improving RIMGIS itself, redesigning the database, developing distribution, and integrating river information systems. Therefore, primary and foreign key, which can distinguish attribute information and entity linkages, were redefined to increase the usability of RIMGIS. Database construction of attribute information and entity relationship diagram have been newly redefined to redesign linkages among tables from the perspective of a river standard database. In addition, this study was undertaken to expand the current supplier-oriented operating system to a demand-oriented operating system by establishing an efficient management of river-related information and a utilization system capable of adapting to the changes of a river management paradigm.

• Korean Journal of Environmental Agriculture
• /
• v.38 no.3
• /
• pp.154-158
• /
• 2019

BACKGROUND: 'Shiranuhi' mandarin is a major cultivar among all late ripening type of citrus, and is widely cultivated in Korea. However, many farmers have reported scion root problems in their orchard resulting in reduced flowering and fruiting. It is necessary that the physiology of scion-rooted 'Shiranuhi' mandarin trees is further understood. METHODS AND RESULTS: This experiment was conducted to understand the growth response and physiology of scion-rooted 'Shiranuhi' mandarin hybrids. In our study, 'Shiranuhi' mandarin trees were divided into two groups: trees without scion roots (control) and trees with scion roots. The experiment was conducted in Seogwipo of Jeju, with ten replicates for each group. Growth of trees with scion roots was more vigorous and the trees were taller than the controls. Tree height and trunk diameter of scion-rooted trees were significantly higher than those of control trees. Exposed length of rootstocks of scion-rooted trees was significantly lower (by about 2 cm) than that of control trees (8.6 cm). In terms of root nutrition, carbon contents of scion-rooted trees was significantly lower than that of control trees, but nitrogen and potassium concentrations in scion roots were significantly higher than those in control roots. CONCLUSION: Based on the results, we infer that growth of scion-rooted trees was very vigorous and the content of nitrogen in these roots was higher than that in the control tree roots. Thus, the carbon/nitrogen ratio of scion roots was significantly lower than that of the control roots.