• Journal of Ocean Engineering and Technology
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• v.37 no.2
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• pp.58-67
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• 2023

While extensive research is being conducted to reduce greenhouse gases in industrial fields, the International Maritime Organization (IMO) has implemented regulations to actively reduce CO₂ emissions from ships, such as energy efficiency design index (EEDI), energy efficiency existing ship index (EEXI), energy efficiency operational indicator (EEOI), and carbon intensity indicator (CII). These regulations play an important role for the design and operation of ships. However, the calculation of the index and indicator might be complex depending on the types and size of the ship. Here, to calculate the EEDI of two target vessels, first, the ships were set as Deadweight (DWT) 50K container and 300K very large crude-oil carrier (VLCC) considering the type and size of those ships along with the engine types and power. Equations and parameters from the marine pollution treaty (MARPOL) Annex VI, IMO marine environment protection committee (MEPC) resolution were used to estimate the EEDI and their changes. Technical measures were subsequently applied to satisfy the IMO regulations, such as reducing speed, energy saving devices (ESD), and onboard CO₂ capture system. Process simulation model using Aspen Plus v10 was developed for the onboard CO₂ capture system. The obtained results suggested that the fuel change from Marine diesel oil (MDO) to liquefied natural gas (LNG) was the most effective way to reduce EEDI, considering the limited supply of the alternative clean fuels. Decreasing ship speed was the next effective option to meet the regulation until Phase 4. In case of container, the attained EEDI while converting fuel from Diesel oil (DO) to LNG was reduced by 27.35%. With speed reduction, the EEDI was improved by 21.76% of the EEDI based on DO. Pertaining to VLCC, 27.31% and 22.10% improvements were observed, which were comparable to those for the container. However, for both vessels, additional measure is required to meet Phase 5, demanding the reduction of 70%. Therefore, onboard CO₂ capture system was designed for both KCS (Korea Research Institute of Ships & Ocean Engineering (KRISO) container ship) and KVLCC2 (KRISO VLCC) to meet the Phase 5 standard in the process simulation. The absorber column was designed with a diameter of 1.2-3.5 m and height of 11.3 m. The stripper column was 0.6-1.5 m in diameter and 8.8-9.6 m in height. The obtained results suggested that a combination of ESD, speed reduction, and fuel change was effective for reducing the EEDI; and onboard CO₂ capture system may be required for Phase 5.

• 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.

• Korean Journal of Ecology and Environment
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• v.56 no.4
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• pp.339-347
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• 2023

Dissolved organic matter (DOM) is a key component in the biogeochemical cycling in freshwater ecosystem. However, it has been rarely explored, particularly complex river watershed dominated by natural and anthropogenic sources, such as various effluent facility and livestock. The current research developed a new analytical method for TOC/TN (Total Organic Carbon/Total Nitrogen) stable isotope ratio, and distinguish DOM source using stable isotope value (δ¹³C-DOC) and spectroscopic indices (fluorescence index [FI] and biological index [BIX]). The TOC/TN-IR/MS analytical system was optimized and precision and accuracy were secured using two international standards (IAEA-600 Caffein, IAEA-CH-6 Sucrose). As a result of controlling the instrumental conditions to enable TOC stable isotope analysis even in low-concentration environmental samples (<1 mgC L^-1), the minimum detection limit was improved. The 12 potential DOM source were collected from watershed, which includes top-soils, groundwater, plant group (fallen leaves, riparian plants, suspended algae) and effluent group (pig and cow livestock, agricultural land, urban, industry facility, swine facility and wastewater treatment facilities). As a result of comparing characteristics between 12 sources using spectroscopic indices and δ¹³C-DOC values, it were divided into four groups according to their characteristics as a respective DOM sources. The current study established the TOC/TN stable isotope analyses system for the first time in Korea, and found that spectroscopic indices and δ¹³C-DOC are very useful tool to trace the origin of organic matter in the aquatic environments through library database.

• Korean Journal of Remote Sensing
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• v.39 no.5_4
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• pp.1075-1084
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• 2023

Satellite-derived data is collected by observing the Earth and is used in various fields such as national defense, natural disasters, location-based services, infrastructure, environment, energy, marine, and insurance. This study aims to present the virtuous cycle structure of the satellite information data industry and the business ecosystem model of the industry. As a research method, cases were collected and categorized from the following areas: literature, online, application, and content. The results show that the ecosystem model of the satellite information data industry provides an approach to content services in public and commercial areas, and develops various algorithmic technologies to facilitate content production and services at the level of complex general-purpose technologies. Second, in terms of content typology, satellite information data can be subdivided into monitoring content, urban space monitoring content, and satellite information content. Third, the consumption value of satellite content could be subdivided into informational value, environmental, social and governance (ESG) value, educational value, and content value. In order to expand the global content market, Korea will need to focus on creating an ecosystem for the satellite information industry and discovering differentiated content. It will also need to increase the popularization and accessibility of data to the general public and promote the Korean K-Satellite Information Data Industry ecosystem through government support, policy efforts, and policies such as establishing legal systems, increasing investment, and training human resources.

• Journal of Navigation and Port Research
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• v.46 no.6
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• pp.483-490
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• 2022

Floating LiDAR is a system that provides a new paradigm for wind condition observation, which is essential when creating an offshore wind farm. As it can save time and money, minimize environmental impact, and even reduce backlash from local communities, it is emerging as the industry standard. However, the design and verification of a stable platform is very important, as disturbance factors caused by fluctuations of the buoy affect the reliability of observation data. In Korea, due to the nation's late entry into the technology, a number of foreign equipment manufacturers are dominating the domestic market. The west coast of Korea is a shallow sea environment with a very large tidal difference, so strong currents repeatedly appear depending on the region, and waves of strong energy that differ by season are formed. This paper conducted a study examining buoys suitable for LiDAR operation in the waters of Korea, which have such complex environmental characteristics. In this paper, we will introduce examples of optimized design and verification of ship-type buoys, which were applied first, and derive important concepts that will serve as the basis for the development of various platforms in the future.

• The Journal of the Korea institute of electronic communication sciences
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• v.18 no.6
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• pp.1009-1014
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• 2023

Comprehensive observations of the Euler method and the Lagrangian method were performed in order to obtain high-resolution observation data in space and time for the complex environment of new city. The two radiosondes, which measure meteorological parameters using Lagrangian methods, produced air pressure, wind speed and wind direction. They were generally consistent with each other even if the observation points or times were different. The temperature measured by the sensor exposed to the air during the day was relatively high as the altitude increased due to the influence of solar radiation. The temporal difference in wind direction and speed was found in the comparison of Euler's wind profiler data with radiosonde data. When the wind field is horizontally in homogeneous, this result implies the need to consider the advection component to compare the data of the two observation methods. In this study, a method of using observation data at different times for each altitude section depending on the observation period of the Euler method is proposed to effectively compare the data of the two observation methods.

• Information Systems Review
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• v.22 no.4
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• pp.185-203
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• 2020

With the advent of 4th industrial revolution, the manufacturing industry is converging with ICT and changing into the era of smart manufacturing. In the smart factory, all machines and facilities are connected based on ICT, and thus security should be further strengthened as it is exposed to complex security threats that were not previously recognized. To reduce the risk of security incidents and successfully implement smart factories, it is necessary to identify key security factors to be applied, taking into account the characteristics of the industrial environment of smart factories utilizing ICT. In this study, we propose a 'hierarchical classification model of security factors in smart factory' that includes terminal, network, platform/service categories and analyze the importance of security factors to be applied when developing smart factories. We conducted an assessment of importance of security factors to the groups of smart factories and security experts. In this study, the relative importance of security factors of smart factory was derived by using AHP technique, and the priority among the security factors is presented. Based on the results of this research, it contributes to building the smart factory more securely and establishing information security required in the era of smart manufacturing.

• Journal of the Korean Society for Library and Information Science
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• v.58 no.2
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• pp.363-384
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• 2024

This study was conducted to examine the user's experiences with the public library in Daejeon using big data analysis, focusing on the text mining technique. To know this, first, the overall evaluation and perception of users about the public library in Daejeon were explored by collecting data on social media. Second, through analysis using online news articles, the pending issues that are being discussed socially were identified. As a result of the analysis, the proportion of users with children was first high. Next, it was found that topics through LDA analysis appeared in four categories: 'cultural event/program', 'data use', 'physical environment and facilities', and 'library service'. Finally, it was confirmed that keywords for the additional construction of libraries and complex cultural spaces and the establishment of a library cooperation system appeared at the core in the news article data. Based on this, it was proposed to build a library in consideration of regional balance and to create a social parenting community network through business agreements with childcare and childcare institutions. This will contribute to identifying the policy and social trends of public libraries in Daejeon and implementing data-based public library operations that reflect local community demands.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.26 no.6
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• pp.51-65
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• 2023

The Jeongmaeks are Korea's unique forest space recognition system that diverged from the Baekdudaegan. The Jeongmaeks are easily exposed to pressure because it is adjacent to the living area. Among them, Nakdong-Jeongmaek has high biodiversity, but damage is accelerating. According to the Convention on Biological Diversity (CBD) in 2022, the target is to expand the area of terrestrial and marine protected areas to 30% of national territory by 2030. As of September 2023, the area of terrestrial protected areas in South Korea is only 16.97% of the country's territory. This is due in part to the high proportion of private forests in the region, which makes it difficult to establish protected areas. Therefore, there is a need to establish Other Effective Area-based Conservation Measure (OECMs), which pursue complex and effective conservation that considers multiple values, as an alternative to protected areas. This study aims to identify areas suitable for OECM and to provide opinions on the establishment of appropriate management plans for each value using SOM and InVEST Habitat Quality model. This study evaluated the habitat quality of 206 villages located within 1km of the Nakdong-Jeongmaek and compared the characteristics of villages classified by SOM. As a result, the habitat quality was 0.867 for Tourism village (ClusterIV), 0.838 for Conservation village (ClusterVI), 0.835 for Mixed village (ClusterI), 0.796 for Production (ClusterV), 0.731 for Rural village (ClusterIII) and 0.625 for Urban village (ClusterII). When the distribution was identified through statistical analysis, the Kruskal-Wallis test showed that the distributions were not identical, with a p-value of 1.53e-08. Dunn's test showed a difference between Tourism, Conservation and Rural, Urban village. However, Mixed village was overestimated due to the lack of villages and the small area included in the study area. Moreover, Conservation village was somewhat under-evaluated in the analysis due to the use of a single weight for protected areas. It is necessary to perform additional reinforcement of the value evaluation of Jeongmaeks by conducting Forest Resource Survey and the National Natural Environment Survey. Therefore, we believe that sufficient validity for the establishment of OECMs in the Nakdong-Jeongmaek can be provided by addressing these limitations and conducting additional research.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.34 no.2
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• pp.207-216
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• 2024

As big data was built due to the 4th Industrial Revolution, personalized services increased rapidly. As a result, the amount of personal information collected from online services has increased, and concerns about users' personal information leakage and privacy infringement have increased. Online service providers provide privacy policies to address concerns about privacy infringement of users, but privacy policies are often misused due to the long and complex problem that it is difficult for users to directly identify risk items. Therefore, there is a need for a method that can automatically check whether the privacy policy is safe. However, the safety verification technique of the conventional blacklist and machine learning-based privacy policy has a problem that is difficult to expand or has low accessibility. In this paper, to solve the problem, we propose a safety verification technique for the privacy policy using the GPT-3.5 API, which is a generative artificial intelligence. Classification work can be performed evenin a new environment, and it shows the possibility that the general public without expertise can easily inspect the privacy policy. In the experiment, how accurately the blacklist-based privacy policy and the GPT-based privacy policy classify safe and unsafe sentences and the time spent on classification was measured. According to the experimental results, the proposed technique showed 10.34% higher accuracy on average than the conventional blacklist-based sentence safety verification technique.