• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.22 no.2
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• pp.1-7
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• 2022

The purpose of this study is to discuss the impact of unmanned aerial vehicle service and how to activate it. The discussion on the impact of the introduction of the unmanned aerial vehicle service was examined in terms of economic, environmental, and social acceptance, and a plan to revitalize the industry was presented. In terms of economic impact, if transportation services are increased using unmanned aerial vehicles in the future, road-based transportation cargo may decrease and road movement speed may increase due to reduced road congestion. This can have a positive effect on the increase in the value of land or real estate assets, and it also provides an impact on smart city design. In terms of environmental impact, unmanned aerial vehicles (UAVs) generally move through electricity, so they emit less exhaust gas compared to other existing devices, such as vehicles and railroads, and thus have less environmental impact. However, noise can have a negative impact on the habitat in the presence of wild animals along their migration routes. In terms of social acceptability of unmanned aerial vehicles (UAV) technology, areas that are declining due to the emergence of new services may appear, and at the same time, organizations that create profits may appear, causing conflicts between industries. Therefore, it is essential to form a social consensus on the acceptance of emerging industries. The government should come up with various countermeasures to minimize the negative impact that reflects the characteristics of the unmanned aerial vehicle use service. Just as various systems such as road signs were introduced so that vehicles can be operated on the ground to secure air routes in the mid- to long-term for revitalization of unmanned-based industries, development and establishment of services that should be introduced and applied prior to constructing air routes I need this. In addition, the design and implementation of information collection and operation plans for unmanned air traffic management in Korea and a plan to secure a control system for each region should also be made. This study can contribute to providing ideas for mid- to long-term research on new areas with the development of the unmanned aerial vehicle industry.

• Journal of the Society of Disaster Information
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• v.18 no.1
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• pp.202-217
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• 2022

Purpose: The recent increased use of Personal Mobility (PM) has been accompanied by a rise in the annual number of accidents. Accordingly, the safety requirements for PM use are being strengthened, but the laws/systems, infrastructure, and management systems remain insufficient for fostering a safe environment. Therefore, this study comprehensively searches the main problems and improvement methods through a review of previous studies that are related to PM. Then the priorities according to the importance of the improvement methods are presented through the Delphi survey. Method: The research method is mainly composed of a literature study and an expert survey (Delphi survey). Prior research and improvement cases (local governments, government departments, companies, etc.) are reviewed to derive problems and improvements, and a problem/improvement classification table is created based on keywords. Based on the classification contents, an expert survey is conducted to derive a priority improvement plan. Result: The PM-related problems were in 'non-compliance with traffic laws, lack of knowledge, inexperienced operation, and lack of safety awareness' in relation to human factors, and 'device characteristics, road-drivable space, road facilities, parking facilities' in relation to physical factors. 'Management/supervision, product management, user management, education/training' as administrative factors and legal factors are divided into 'absence/sufficiency of law, confusion/duplication, reduced effectiveness'. Improvement tasks related to this include 'PM education/public relations, parking/return, road improvement, PM registration/management, insurance, safety standards, traffic standards, PM device safety, PM supplementary facilities, enforcement/management, dedicated organization, service providers, management system, and related laws/institutional improvement', and 42 detailed tasks are derived for these 14 core tasks. The results for the importance evaluation of detailed tasks show that the tasks with a high overall average for the evaluation items of cost, time, effect, urgency, and feasibility were 'strengthening crackdown/instruction activities, education publicity/campaign, truancy PM management, and clarification of traffic rules'. Conclusion: The PM market is experiencing gradual growth based on shared services and a safe environment for PM use must be ensured along with industrial revitalization. In this respect, this study seeks out the major problems and improvement plans related to PM from a comprehensive point of view and prioritizes the necessary improvement measures. Therefore, it can serve as a basis of data for future policy establishment. In the future, in-depth data supplementation will be required for each key improvement area for practical policy application.

• Journal of the Daesoon Academy of Sciences
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• v.37
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• pp.1-52
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• 2021

The Naejeong, the inner court, which is one of the structures found in the temple complexes of Daesoon Jinrihoe. It serves the function of leading and controlling the operation and direction of Korean religions in general. Considering that the dictionary meaning of 'Naejeong' is 'a place to manage the affairs of the state from inside a palace,' the name and function of the structure appear to be in harmony. However, in the Daesoon Jinrihoe context, it is said that the name 'Naejeong (內庭 'Neiting' in Chinese)' is related to a verse from a Daoist scripture. It has not been revealed whether or not the scripture is historical, and what contents or contextual meanings it contains. This study tries to pursue this matter and introduce the original source of the Naejeong in Daesoon Jinrihoe as likely coming from Qianbapinxianjing (前八品仙經, The Former Scripture of the Eight Phases That Reveal the Means to Acquire Immortality). This scripture was compiled in Lüzu-quanshu(呂祖全書, The Entire Collection of Ancestor Lü). This text and its contextual meanings will also be examined. The origin of Qianbapinxianjing dates back to either the late Ming Dynasty or the early Qing. In those days, there existed a group of literati who worshipped Ancestor Lü because he had saved people and taught the art of immortality. The group organized Daoist Spirit-Writing Altars (鸞壇道敎) and invoked the spirit of Ancestor Lü. They were said to have been taught through messages received from spirit-writing sessions (降乩) with Ancestor Lü and several Daoist scriptures were composed by them in this manner. At Immortals-Gathering Pavilion (集仙樓) of Wandian (萬店) in Guangling (廣陵), China, some literati in that group conducted a spirit-writing session with Ancestor Lü between 1589 and 1626, and they produced a scripture which contained the passage, "A crow and a rabbit gather in the middle valley (烏兎結中谷) while a turtle entwined with a snake is in the inner court (龜蛇盤內庭)." They titled the scripture, The Five Movements and Filial Piety (五行端孝). This passage symbolically expresses the accomplishment of immortality in Neidan (internal alchemy) which, within the human body, combines the two energies of yin and yang which are Water and Fire in the Five Movements scheme. This kind of cultivation is said to be achieved only by maintaining the highest possible degree of filial piety. In this context, the Naejeong where a turtle is entwined with a snake (龜蛇合體) was a term that symbolically depicted a place wherein one transforms into an immortal through cultivation. The Five Movements and Filial Piety was included in Qianbapinxianjing after it had been compiled with the other scriptures containing Ancestor Lü's teachings. In 1744, Qianbapinxianjing was included in Lüzu-quanshu, the entire 32-volume collection of Ancestor Lü and printed for the first time. This underlies the belief in Ancestor Lü (呂祖信仰) which embraces the idea of the redemption of people, teaches the arts of immortality, and features Daoist Spirit-Writing Altars, filial piety, the art of Neidan, and the combination of Water and Fire.

• Journal of the Korean Institute of Gas
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• v.26 no.3
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• pp.45-53
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• 2022

In order to improve the emission of diesel engines, natural gas-diesel dual fuel combustion compression ignition engines are in the spotlight. In particular, a reactivity controlled compression ignition (RCCI) combustion strategy is investigated comprehensively due to its possibility to improve both efficiency and emissions. With advanced diesel direct injection timing earlier than TDC, it achieves spontaneous reaction with overall lean mixture from a homogeneous mixture in the entire cylinder area, reducing nitrogen oxides (NOx) and particulate matter (PM) and improving braking heat efficiency at the same time. However, there is a disadvantage in that the amount of incomplete combustion increases in a low load region with a relatively small amount of fuel-air. To solve this, sensitive control according to the diesel injection timing and fuel ratio is required. In this study, experiments were conducted to improve efficiency and exhaust emissions of the natural gas-diesel dual fuel engine at low load, and evaluate combustion stability according to the diesel injection timing at the operation point for power generation. A 6 L-class commercial diesel engine was used for the experiment which was conducted under a 50% load range (~50 kW) at 1,800 rpm. Two injectors with different spray patterns were applied to the experiment, and the fraction of natural gas and diesel injection timing were selected as main parameters. Based on the experimental results, it was confirmed that the brake thermal efficiency increased by up to 1.3%p in the modified injector with the narrow-angle injection added. In addition, the spray pattern of the modified injector was suitable for premixed combustion, increasing operable range in consideration of combustion instability, torque reduction, and emissions level under Tier-V level (0.4 g/kWh for NOx).

• Journal of Korea Port Economic Association
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• v.37 no.4
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• pp.161-173
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• 2021

The shipping industry plummeted and was depressed due to the global economic crisis caused by the bankruptcy of Lehman Brothers in the US in 2008. In 2020, the shipping market also suffered from a collapse in the unstable global economic situation due to the COVID-19 pandemic, but unexpectedly, it changed to an upward trend from the end of 2020, and in 2021, it exceeded the market of the boom period of 2008. According to the Clarksons report published in May 2021, the decrease in cargo volume due to the COVID-19 pandemic in 2020 has returned to the pre-corona level by the end of 2020, and the tramper bulk carrier capacity of 103~104% of the Panamax has been in the ports due to congestion. Earnings across the bulker segments have risen to ten-year highs in recent months. In this study, as factors affecting BDI, the capacity and congestion ratio of Cape and Panamax ships on the supply side, iron ore and coal seaborne tonnge on the demand side and Granger causality test, IRF(Impulse Response Function) and FEVD(Forecast Error Variance Decomposition) were performed using VAR model to analyze the impact on BDI by congestion caused by strengthen quarantine at the port due to the COVID-19 pandemic and the loading and discharging operation delay due to the infection of the stevedore, etc and to predict the shipping market after the pandemic. As a result of the Granger causality test of variables and BDI using time series data from January 2016 to July 2021, causality was found in the Fleet and Congestion variables, and as a result of the Impulse Response Function, Congestion variable was found to have significant at both upper and lower limit of the confidence interval. As a result of the Forecast Error Variance Decomposition, Congestion variable showed an explanatory power upto 25% for the change in BDI. If the congestion in ports decreases after With Corona, it is expected that there is down-risk in the shipping market. The COVID-19 pandemic occurred not from economic factors but from an ecological factor by the pandemic is different from the past economic crisis. It is necessary to analyze from a different point of view than the past economic crisis. This study has meaningful to analyze the causality and explanatory power of Congestion factor by pandemic.

• Korean Journal of Remote Sensing
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• v.38 no.5_3
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• pp.925-938
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• 2022

Agricultural reservoirs are an important water resource nationwide and vulnerable to abnormal climate effects such as drought caused by climate change. Therefore, it is required enhanced management for appropriate operation. Although water-level tracking is necessary through continuous monitoring, it is challenging to measure and observe on-site due to practical problems. This study presents an objective comparison between multiple AI models for water-body extraction using radar images that have the advantages of wide coverage, and frequent revisit time. The proposed methods in this study used Sentinel-1 Synthetic Aperture Radar (SAR) images, and unlike common methods of water extraction based on optical images, they are suitable for long-term monitoring because they are less affected by the weather conditions. We built four AI models such as Support Vector Machine (SVM), Random Forest (RF), Artificial Neural Network (ANN), and Automated Machine Learning (AutoML) using drone images, sentinel-1 SAR and DSM data. There are total of 22 reservoirs of less than 1 million tons for the study, including small and medium-sized reservoirs with an effective storage capacity of less than 300,000 tons. 45 images from 22 reservoirs were used for model training and verification, and the results show that the AutoML model was 0.01 to 0.03 better in the water Intersection over Union (IoU) than the other three models, with Accuracy=0.92 and mIoU=0.81 in a test. As the result, AutoML performed as well as the classical machine learning methods and it is expected that the applicability of the water-body extraction technique by AutoML to monitor reservoirs automatically.

• Journal of Korea Water Resources Association
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• v.55 no.8
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• pp.623-634
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• 2022

Due to river maintenance projects such as the creation of hydrophilic areas around rivers and the Four Rivers Project, the flow characteristics of rivers are continuously changing, and the risk of water quality accidents due to the inflow of various pollutants is increasing. In the event of a water quality accident, it is necessary to minimize the effect on the downstream side by predicting the concentration and arrival time of pollutants in consideration of the flow characteristics of the river. In order to track the behavior of these pollutants, it is necessary to calculate the diffusion coefficient and dispersion coefficient for each section of the river. Among them, the dispersion coefficient is used to analyze the diffusion range of soluble pollutants. Existing experimental research cases for tracking the behavior of pollutants require a lot of manpower and cost, and it is difficult to obtain spatially high-resolution data due to limited equipment operation. Recently, research on tracking contaminants using RGB drones has been conducted, but RGB images also have a limitation in that spectral information is limitedly collected. In this study, to supplement the limitations of existing studies, a hyperspectral sensor was mounted on a remote sensing platform using a drone to collect temporally and spatially higher-resolution data than conventional contact measurement. Using the collected spatio-temporal hyperspectral images, the tracer concentration was calculated and the transverse dispersion coefficient was derived. It is expected that by overcoming the limitations of the drone platform through future research and upgrading the dispersion coefficient calculation technology, it will be possible to detect various pollutants leaking into the water system, and to detect changes in various water quality items and river factors.

• Journal of the Korea Organic Resources Recycling Association
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• v.29 no.4
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• pp.67-76
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• 2021

Biogasification is a technology that produces environmentally friendly fuel using methane gas generated in the process of stably decomposing and processing organic waste. Biogasification is the most used method for energy conversion of organic waste with high moisture content, and is a useful method for organic waste treatment following the prohibition of direct landfill (2005) and marine dumping (2013). Due to African Swine Fever (ASF), which recently occurred in Korea, recycling of wet feed is prohibited, and consumers such as dry feed and compost are negatively recognized, making it difficult to treat food waste. Accordingly, biogasification is attracting more attention for the treatment and recycling of food waste. Korea's energy consumption amounted to 268.41 106toe, ranking 9th in the world. However, it is an energy-poor country that depends on foreign imports for about 95.8% of its energy supply. Therefore, in Korea, the Renewable Energy Portfolio Standard (RPS) is being introduced. The domestic RPS system sets the weight of the new and renewable energy certificate (REC, Renewable energy certificate) of waste energy lower than that of other renewable energy. Therefore, an additional incentive system is required for the activation of waste-to-energy. In this study, the operation of an anaerobic digester that treats food waste, food waste Leachate and various organic wastes was confirmed. It was intended to be used as basic data for preparing the waste-to-energy incentive system through precise monitoring for a certain period of time. Four sites that produce biogas from organic waste and use them for power generation and heavy gas were selected as target facilities, and field surveys and sampling were conducted. Basic properties analysis was performed on the influent sample of organic waste and the effluent sample according to the treatment process. As a result of the analysis of the properties, the total solids of the digester influent was an average of 12.11%, and the volatile solids of the total solids were confirmed to be 85.86%. BOD and CODcr removal rates were 60.8% and 64.8%. The volatile fatty acids in the influent averaged 55,716 mg/L. It can be confirmed that most of the volatile fatty acids were decomposed and removed with an average reduction rate of 92.3% after anaerobic digestion.

• Journal of the Korean Society of Marine Environment & Safety
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• v.28 no.7
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• pp.1216-1221
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• 2022

Ships tend to be larger to increase the efficiency of cargo transportation. Larger ships lead to increased travel time for ship workers, increased work intensity, and reduced work efficiency. Problems such as increased work intensity are reducing the influx of young people into labor, along with the phenomenon of avoidance of high intensity labor by the younger generation. In addition, the rapid aging of the population and decrease in the young labor force aggravate the labor shortage problem in the maritime industry. To overcome this, the maritime industry has recently introduced technologies such as an intelligent production design platform and a smart production operation management system, and a smart autonomous logistics system in one of these technologies. The smart autonomous logistics system is a technology that delivers various goods using intelligent mobile robots, and enables the robot to drive itself by using sensors such as lidar and camera. Therefore, in this paper, it was checked whether the mobile robot could autonomously drive to the stop sign by detecting the passage way of the ship deck. The autonomous driving was performed by detecting the passage way of the ship deck through the camera mounted on the mobile robot based on the data learned through Nvidia's End-to-end learning. The mobile robot was stopped by checking the stop sign using SSD MobileNetV2. The experiment was repeated five times in which the mobile robot autonomously drives to the stop sign without deviation from the ship deck passage way at a distance of about 70m. As a result of the experiment, it was confirmed that the mobile robot was driven without deviation from passage way. If the smart autonomous logistics system to which this result is applied is used in the marine industry, it is thought that the stability, reduction of labor force, and work efficiency will be improved when workers work.

• Journal of Intelligence and Information Systems
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• v.29 no.1
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• pp.121-142
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• 2023

As the number and weight of imported food are steadily increasing, safety management of imported food to prevent food safety accidents is becoming more important. The Ministry of Food and Drug Safety conducts on-site inspections of foreign food facilities before customs clearance as well as import inspection at the customs clearance stage. However, a data-based safety management plan for imported food is needed due to time, cost, and limited resources. In this study, we tried to increase the efficiency of the on-site inspection by preparing a machine learning prediction model that pre-selects the companies that are expected to fail before the on-site inspection. Basic information of 303,272 foreign food facilities and processing businesses collected in the Integrated Food Safety Information Network and 1,689 cases of on-site inspection information data collected from 2019 to April 2022 were collected. After preprocessing the data of foreign food facilities, only the data subject to on-site inspection were extracted using the foreign food facility_code. As a result, it consisted of a total of 1,689 data and 103 variables. For 103 variables, variables that were '0' were removed based on the Theil-U index, and after reducing by applying Multiple Correspondence Analysis, 49 characteristic variables were finally derived. We build eight different models and perform hyperparameter tuning through 5-fold cross validation. Then, the performance of the generated models are evaluated. The research purpose of selecting companies subject to on-site inspection is to maximize the recall, which is the probability of judging nonconforming companies as nonconforming. As a result of applying various algorithms of machine learning, the Random Forest model with the highest Recall_macro, AUROC, Average PR, F1-score, and Balanced Accuracy was evaluated as the best model. Finally, we apply Kernal SHAP (SHapley Additive exPlanations) to present the selection reason for nonconforming facilities of individual instances, and discuss applicability to the on-site inspection facility selection system. Based on the results of this study, it is expected that it will contribute to the efficient operation of limited resources such as manpower and budget by establishing an imported food management system through a data-based scientific risk management model.