KIPS Transactions on Computer and Communication Systems
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v.12
no.10
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pp.309-318
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2023
Recently, each country has been moving to introduce an LCA (Life Cycle Assessment) to regulate greenhouse gas emissions. The LCA is a mean of measuring and evaluating greenhouse gas emissions generated over the entire life cycle of a vehicle. Reliable data for each electric vehicle component is needed to increase the reliability of the LCA results. To this end, studies on life cycle evaluation models using blockchain technology have been conducted. However, in the existing model, key product information is exposed to other participants. And each time parts data information is updated, it must be recorded in the blockchain ledger in the form of a transaction, which is inefficient. In this paper, we proposed a DID(Decentralized Identity)-based data collection model for LCA to collect vehicle component data and verify its validity effectively. The proposed model increases the reliability of the LCA by ensuring the validity and integrity of the collected data and verifying the source of the data. The proposed model guarantees the validity and integrity of collected data. As only user authentication information is shared on the blockchain ledger, the model prevents indiscriminate exposure of data and efficiently verifies and updates the source of data.
This study forecasted the manpower demand of eco-friendly smart shipbuilding, whose importance and weight are increasing according to the environmental regulations of the IMO and the spread of the 4th industrial revolution technology. It predicted the shipbuilding industry manpower by applying various models of trend analysis and time series analysis based on data from 2000 to 2020 of Statistics Korea. It was found that the prediction applying geometric mean had the smallest gap among the trend and time series analysis methods in comparing between forecast results and actual data for the past 5 years. Therefore, the demand for manpower in the shipbuilding industry was predicted by using the geometric mean method. In addition, the manpower demand of smart eco-friendly ships wast forecasted by using the 2018 and 2020 manpower survey results of the Ministry of Trade, Industry and Energy and reflecting the trend of manpower increase in the shipbuilding industry. The result of forecasting showed that 62,001 person in 2025 and 85,035 people in 2030. This study is expected to contribute to the adjustment of manpower supply and demand and the training professional manpower in the future by increasing the accuracy of forecasting for high value-added eco-friendly smart ships.
Proceedings of the Korean Institute of Navigation and Port Research Conference
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2023.11a
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pp.116-118
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2023
In recent years, the need for economical and sustainable ship routing has emerged due to the enforced regulations on environmental issues. Despite the development of weather forecasting technology, maritime accidents by rough waves have continued to occur due to incorrect weather forecasts. In this study, onboard measurements are conducted to observe the acutal situation on merchant ships in operation encountering rough waves. The types of measured data include information related to navigation (Ship's position, speed, bearing, rudder angle) and engine (engine revolutions, power, shaft thrust, fuel consumption), weather conditions (wind, waves), and ship motions (roll, pitch, and yaw). These ship experiments was conducted to 28,000 DWT bulk carrier, 63,000 DWT bulk carrier, 20,000 TEU container ship, and 12,000 TEU container ship. The actual ship experiment of each ship is intended to acquire various types of data and utilize them for multi-objective studies related to ship operation. Additionally, in order to confirm the sea conditions, the directional wave spectrum was reproduced using a wave simulation model. Through data collection from ship experiments and wave simulations, various studies could be proceeding such as the measurement for accurate wave information by marine radar and analysis for cargo collapse accidents. In addition, it is expected to be utilized in various themes from the perspective of safety and efficiency in ship operation.
Following the signing of the Paris Agreement on Climate Change (UNFCCC, 2015), the world is expanding greenhouse gas reduction activities through comprehensive participation that includes not only developed countries but also developing countries. Major countries around the world are placing high expectations on the effectiveness of total carbon emissions regulation through the carbon emissions market. However, in order to obtain carbon credits, third-party verification is required based on quantitative carbon reduction data. Accordingly, in this paper, we developed an AIoT high-efficiency street light for carbon emissions and conducted a performance analysis study to measure the luminous efficiency of the lighting fixture. To obtain carbon emissions rights, we used high-efficiency LED PKG, developed our own high-voltage PFC, and developed high-efficiency lighting fixtures capable of communication. For communication, the 2.4GHz LoRa method was adopted between the lighting fixture and the gateway. Lens design was conducted through simulation of Korea Expressway Corporation's standard streetlight types A, B, and C. The performance of the streetlight was verified as being more efficient than other existing products through the measurement of luminous efficiency by an accredited rating agency, and it is expected that carbon emissions rights will be obtained by reducing electrical energy through this.
The conservation and restoration of wetlands are essential tasks for the sustainable development of human society and the environment, providing vital benefits such as biodiversity maintenance, natural disaster mitigation, and climate change alleviation. This study aims to analyze the strategic interactions and interests among various stakeholders using game theory and to provide significant grounds for policy decisions related to wetland restoration and development. In this study, hypothetical scenarios were set up for three types of cities: large, medium, and small. Stakeholders such as governments, development companies, environmental groups, and local residents were identified. Strategic options for each stakeholder were developed, and a payoff matrix was established through discussions among wetland ecology experts. Subsequently, non-cooperative game theory was applied to analyze Nash equilibria and Pareto efficiency. In large cities, strategies of 'Wetland Conservation' and 'Eco-Friendly Development' were found beneficial for all stakeholders. In medium cities, various strategies were identified, while in small cities, 'Eco-Friendly Development' emerged as the optimal solution for all parties involved. The Pareto efficiency analysis revealed how the optimal solutions for wetland management could vary across different city types. The study highlighted the importance of wetland conservation, eco-friendly development, and wetland restoration projects for each city type. Accordingly, policymakers should establish regulations and incentives that harmonize environmental protection and urban development and consider programs that promote community participation. Understanding the roles and strategies of stakeholders and the advantages and disadvantages of each strategy is crucial for making more effective policy decisions.
This study uses Node2vec graph embedding method and Light GBM link prediction to explore undeveloped export candidate countries in Korea's food and beverage industry. Node2vec is the method that improves the limit of the structural equivalence representation of the network, which is known to be relatively weak compared to the existing link prediction method based on the number of common neighbors of the network. Therefore, the method is known to show excellent performance in both community detection and structural equivalence of the network. The vector value obtained by embedding the network in this way operates under the condition of a constant length from an arbitrarily designated starting point node. Therefore, it has the advantage that it is easy to apply the sequence of nodes as an input value to the model for downstream tasks such as Logistic Regression, Support Vector Machine, and Random Forest. Based on these features of the Node2vec graph embedding method, this study applied the above method to the international trade information of the Korean food and beverage industry. Through this, we intend to contribute to creating the effect of extensive margin diversification in Korea in the global value chain relationship of the industry. The optimal predictive model derived from the results of this study recorded a precision of 0.95 and a recall of 0.79, and an F1 score of 0.86, showing excellent performance. This performance was shown to be superior to that of the binary classifier based on Logistic Regression set as the baseline model. In the baseline model, a precision of 0.95 and a recall of 0.73 were recorded, and an F1 score of 0.83 was recorded. In addition, the light GBM-based optimal prediction model derived from this study showed superior performance than the link prediction model of previous studies, which is set as a benchmarking model in this study. The predictive model of the previous study recorded only a recall rate of 0.75, but the proposed model of this study showed better performance which recall rate is 0.79. The difference in the performance of the prediction results between benchmarking model and this study model is due to the model learning strategy. In this study, groups were classified by the trade value scale, and prediction models were trained differently for these groups. Specific methods are (1) a method of randomly masking and learning a model for all trades without setting specific conditions for trade value, (2) arbitrarily masking a part of the trades with an average trade value or higher and using the model method, and (3) a method of arbitrarily masking some of the trades with the top 25% or higher trade value and learning the model. As a result of the experiment, it was confirmed that the performance of the model trained by randomly masking some of the trades with the above-average trade value in this method was the best and appeared stably. It was found that most of the results of potential export candidates for Korea derived through the above model appeared appropriate through additional investigation. Combining the above, this study could suggest the practical utility of the link prediction method applying Node2vec and Light GBM. In addition, useful implications could be derived for weight update strategies that can perform better link prediction while training the model. On the other hand, this study also has policy utility because it is applied to trade transactions that have not been performed much in the research related to link prediction based on graph embedding. The results of this study support a rapid response to changes in the global value chain such as the recent US-China trade conflict or Japan's export regulations, and I think that it has sufficient usefulness as a tool for policy decision-making.
Jeong, Jongtae;Baik, Min-Hoon;Park, Chung-Kyun;Park, Tae-Jin;Ko, Nak-Youl;Yoon, Ki Hoon
Journal of Nuclear Fuel Cycle and Waste Technology(JNFCWT)
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v.12
no.3
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pp.217-233
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2014
Securing the radiological safety is a prerequisite for the safe management of the naturally occurring radioactive materials (NORM) which cannot be reused. This becomes a crucial focus of our R&D efforts upon the implementation of the Act on Protective Action Guidelines against Radiation in the Natural Environment. To secure the safety, the establishment of technical bases and procedures for securing radiological safety related to the disposal of NORM is required. Thus, it is necessary to analyze the characteristics, to collect the data, to have the radiological safety assessment methodologies and tools, to investigate disposal methods and facilities, and to study the effects of the input data on the safety for the NORM wastes. Here, we assess the environmental impact of the NORM waste disposal with respect to the major domestic and foreign NORM characteristics. The data associated with major industries are collected/analyzed and the status of disposal facilities and methodologies relevant to the NORM wastes is investigated. We also suggest the conceptual design concept of a landfill disposal facility and the management plan with respect to the major NORM wastes characteristics. The radionuclide pathways are identified for the atmospheric transport and leachate release and the environmental impact assessment methodology for the NORM waste disposal is established using a relevant code. The assessment and analysis on the exposure doses and excessive cancer risks for the NORM waste disposal are performed using the characteristics of the representative domestic NORM wastes including flying ash, phosphor gypsum, and redmud. The results show that the exposure dose and the excessive cancer risks are very low to consider any radiation effects. This study will contribute to development in the areas of the regulatory technology for securing radiological safety relevant to NORM waste disposal and to the implementation technology for the Act.
The amount of swine wastewater reaches about $197,000m^3$ per day at live-stock houses in the whole country. A half of the swine wastewater resources are too small to be restricted legally. This untreated wastewater causes the eutrophication in the water bodies. In case of swine wastewater treatment, the solid-liquid separation must be performed because feces(solid phase) and urine(liquid phase) have large differences in nitrogen and phosphorus concentration. It is necessary to assess exactly the concentration of the pollutants in swine wastewater for planning the wastewater treatment facilities. A full-scale operation was carried out in K city and the plant is consists of conventional plant, the supplementary flocculation basin of chemical treatment process and $anaerobic{\cdot}aerobic$ basin for nitrogen removal. The improved full-scale swine wastewater treatment plant removed the $1,500{\sim}3,000mg/l$ of total-nitrogen(T-N) to 120mg/l of T-N and $131{\sim}156mg/l$ of total-phosphorus(T-P) to $0.15{\sim}1.00mg/l$ of T-N. Accordingly, as a results of operational improvement, the removal efficiencies of T-N and T-P were over $92{\sim}96%$, 99%, respectively. The continuous supply of organic carbon sources and the state of pH played important roles for the harmonious metabolism in anaerobic basin and the pH value of anaerobic basin maintained at about 9.0 for the period of the study.
Papaya (Carica papaya L.) is one of the crops widely planted in tropical and subtropical areas. The papaya fruit has low calories and are plentiful in vitamins A and C and in minerals. A major problem in papaya production is a plant disease caused by the papaya ringspot virus (PRSV). The first PRSV-resistant GM papaya expressing a PRSV coat protein gene was developed by USA scientists in 1992. The first commercial GM papaya cultivars derived from the event was approved by the US government in 1997. Development of transgenic papayas has been focused on vaccine production and limited agricultural traits, including insect and pathogen resistance, long shelf life, and aluminum and herbicide tolerance. Approximately 17 countries, including the USA and China, produced transgenic papayas and/or commercialized them, which provoked studies on biosafety assessment and development of GM-detection technologies. For the biosafety assessment of potential effects on human health, effects of long-term feeding to model animals have been studied in terms of toxicity and allergenicity. Studies on environmental safety assessment include influence on soil-microbial biodiversity and transfer to soil bacteria of GM selection markers. Many countries, such as Korea, the European Union, and Japan, that have strict regulations for GM crops have serious concerns about unintended introduction of GM cultivars and food commodities using unauthorized GM crops. Transgene- and/or GM event-specific molecular markers and technologies for genomics-based detection of unauthorized GM papaya have been developed and have resulted in the robust detection of GM papayas.
Safety Management System is the aviation industry policy for while operating the aircraft, to ensure the safety crew, aircraft and passengers. For operating a safe aircraft, in order to establish the international technical standards, the International Civil Aviation Organization has established the Annex 19 of the Convention on International Civil Aviation. As a result, member country was supposed to be in accordance with the policy of the International Civil Aviation Organization, to accept the international standard of domestic air law. The South Korean government announced that it would promote active safety management strategy in primary aviation policy master plan of 2012. And, by integrating and state safety programmes(ssp) and safety management system(sms) for the safe management of Annex 19 is to enforce the policy on aviation safety standards. State safety programmes(ssp) is a system of activities for the aim of strengthening the safety and integrated management of the activities of government. State safety programmes(ssp) is important on the basis of the data of the risk information. Collecting aviation hazard information is necessary for efficient operation of the state safety programmes(ssp) Korean government must implement the strategy required to comply with aviation methods and standards of the International Civil Aviation Organization. Airlines, must strive to safety features for safety culture construction and improvement of safety management is realized. It is necessary to make regulations on the basis of the aviation practice, for aviation safety regulatory requirements, aviation safety should reflect the opinion of the aviation industry.
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