Smart sewage treatment plant means creating a safe and clean water environment by establishing an ICT-based real-time monitoring, remote control management and intelligent system for the entire sewage treatment process. The core technology of such a smart sewage treatment plant can be operation control technology using measuring instruments. This research team analyzed and suggested the operation control technologies necessary for the establishment of the intelligent business by referring to the intelligent research projects of the sewage treatment plant in progress in Korea. As a result of the analysis, a total of six removal technologies were presented, including control by scale, reflow water control, linked treated water control, chemical quantity control, winter operation control, and total organic carbon control. By size, standards that can be classified into small and medium-sized large-scale are presented, and in the case of reflow water control, the location of water quality and flow sensors capable of managing reflow water is suggested. In the case of the linked treated water control, the influence and control points of the linked treated water on the sewage treatment plant were presented, and in the case of the chemical injection volume control, a system capable of optimizing the amount of chemical injection according to the introduction of an intelligent sewage treatment plant was presented. In the case of winter operation, the sensors and pumps to be controlled are suggested when considering the decrease in nitrification due to the decrease in water temperature. In the case of total organic carbon control, an interlocking system considering the total amount of pollution in the future was proposed. These operation control scenarios are expected to be used as basic data to be used in intelligent sewage treatment algorithms and scenarios in the future.
The Journal of the Convergence on Culture Technology
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v.7
no.4
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pp.765-778
/
2021
The purpose of this study is to prevent fire accidents in advance by deriving prior knowledge among groups about temporary fire-fighting facilities of workers at construction sites and devising appropriate improvement measures. The findings are as follows.First, in the case of fire extinguishers, statistical attention was paid to the contractor, supervisor, partner worker and fire extinguisher manager between designations. 87% of fire managers and 70% of facility supervisors said fire extinguisher management managers needed to be designated for each type of construction, which requires designation of fire extinguisher management managers, frequently checking and relocating. Second, in the case of simple fire extinguishing facilities, statistical attention was paid to the application of penalties for unauthorized use of fire extinguishing facilities with construction companies, supervisors, and business partners.Third, in the case of emergency alarm measures, statistical attention was paid to the application of emergency alarm sound to temporary broadcasting facilities with construction works, supervisors, and business partners.Fourth, in the case of induction, statistical attention was paid to the application of connection between construction works, supervisors, and partner workers, such as passage guidance, emergency lighting, etc.It was found that 65% of construction workers and 55% of electrical workers had different applications such as aisle guidance and emergency lighting for each type of business partner. In order to resolve blind spots such as evacuation zone guidance due to the structure of the building, it is necessary to easily distinguish the direction of the entrance door from a long distance by applying it in conjunction with passage guidance lights and emergency lighting.
Kim, Kwang Myung;Park, Hyoung June;Lee, Jae Beom;Park, Chan Jin
The Journal of Engineering Geology
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v.32
no.2
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pp.221-239
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2022
Unknown geotechnical characteristics are key challenges in the design of piles for the plant, civil and building works. Although the N-values which were read through the standard penetration test are important, those N-values of the whole area are not likely acquired in common practice. In this study, the N-value is predicted by means of regression analysis with artificial intelligence (AI). Big data is important to improve learning performance of AI, so circular augmentation method is applied to build up the big data at the current study. The optimal model was chosen among applied AI algorithms, such as artificial neural network, decision tree and auto machine learning. To select optimal model among the above three AI algorithms is to minimize the margin of error. To evaluate the method, actual data and predicted data of six performed projects in Poland, Indonesia and Malaysia were compared. As a result of this study, the AI prediction of this method is proven to be reliable. Therefore, it is realized that the geotechnical characteristics of non-boring points were predictable and the optimal arrangement of structure could be achieved utilizing three dimensional N-value distribution map.
Kim, D.H.;Kim, Y.B.;Koo, H.J.;Baek, H.J.;Lee, S.B.;Chang, K.J.
Journal of Practical Agriculture & Fisheries Research
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v.23
no.1
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pp.31-36
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2021
Cytotoxicity was evaluated in A549 lung cancer cells and RAW264.7 macrophage cells with processed aconitum, ginseng, ginger and licorice extracts. The first experiment began to affect toxicity from 100 ㎍/ml concentrations in extracts mixed with processed aconitum and ginseng. Cytotoxicity began at 1000 ㎍/ml concentrations in the second experimental extract with additional ginger, both in the first and second groups affected greater cytotoxicity in lung cancer cells than in macrophage cells, and in the third experimental extract with additional ginger and licorice. In conclusion, when using aconitum, ginseng, ginger, and licorice work in combination, which resulted in less impact on macrophage cells toxicity and more cytotoxicity in certain lung cancer cells.
Journal of Practical Agriculture & Fisheries Research
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v.23
no.1
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pp.49-57
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2021
As the world marks the adoption of the landmark Paris Agreement on climate change, a promising movement for carbon neutrality is taking shape. This agreement would be needed to build a truly global coalition for carbon neutrality by 2050. Greenhouse gas(GHGs) emissions from agriculture come from livestock such as cows, agricultural soils and rice production has been reported by 10% in 2019. Rice cultivation would be reduced a GHGs and thus this research has conducted to minimize the emission of greenhouse gas with the mulching methodology using a biodegradable film in dry hill seeded rice and to conserve the environment through a cultural and ecological weed control instead of chemicals. We have developed the 5th mulching dry hill seeder with the biodegradable film to determine the possibility of stable rice cultivation. There were so many difficulties and constraints in the field operations such as film mulching, hill seeding and effective weed control. The mulching dry hill seeder was so good performance in the 5th trial but the biodegradable film tested was so faster in terms of biodegradation before the heading stage of the rice plant and thus there was not highly effective weed control which is ongoing research with a good performance since 2020.
Journal of Practical Agriculture & Fisheries Research
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v.23
no.1
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pp.5-12
/
2021
In order to extract the essential oil contained in the Elsholtzia splendense Nakai, a fully-bloomed individual was collected and the living body was used for the experiment. Plants were divided into 0.7kg of flowers and 1.5kg of leaves + stems, and extracted by parts and used for scent pattern analysis, and extracted after adding 5kg of outpost for the analysis of essential oil components. Essential oil extraction was performed using the SDE method improved by Schultz et al. (1977), and the extraction time was limited to 1 hour after the material started boiling. The extracted essential oil component was analyzed for fragrance pattern analysis using an e-nose, and the results of analyzing the substance of the essential oil component by GC-MS are as follows. 1. As for the fragrance pattern analysis, in the case of essential oils extracted from flowers, the scent quality was the best at 10-20 minutes, and the scents extracted from stems and leaves were somewhat of poor scent quality, but the fragrance was good at 10-40 minutes. The intensity of scent was the strongest in 10-20 minutes, and the intensity of incense was high even in 30-40 minutes. The scent extracted from the stems and leaves was generally not strong, but appeared high in 10 to 20 minutes. 2. There were 40 kinds of essential oils contained in Elsholtzia splendense Nakai oil. Among them, Mequinol, Benzene, 1,2,3,4-tetramethyl, Elsholtziaketone, and Dehydroelsholtziaketone were identified.
Choi, Hyo Sim;Hong, Jin Su;Lee, Geon Il;Kim, Yoo Yong
Korean Journal of Poultry Science
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v.49
no.2
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pp.61-67
/
2022
The effects of dietary exogenous hydrophilic emulsifiers on the growth, nutrient digestibility, and carcass characteristics of broilers were evaluated. A total of 200 one-day-old broilers (Ross 308) were allotted to one of four treatment groups in a randomized complete block design in five replicates with 10 birds per pen during a 5-week growth experimental period. Birds were fed a corn-soybean meal-based diet with or without the addition of 0.025, 0.050, or 0.075% exogenous hydrophilic emulsifiers. The diets contained 3,025 and 3,075 metabolizable energy/kg for Phases 1 and 2, respectively. For each phase and the overall experimental period, body weight gain (linear, P<0.05) and feed conversion ratio (linear, P<0.05) improved in proportion to the dietary exogenous hydrophilic emulsifier level, while the average daily feed intake was not affected by dietary treatment. Improvement in growth performance by dietary treatments was observed during the last two weeks rather than the first three weeks of the growth phase. In carcass traits, abdominal fat content increased as dietary exogenous hydrophilic emulsifier level increased (linear, P<0.05), whereas dietary emulsifier level did not affect the relative weight of the liver, breast, and leg muscles. In conclusion, addition of dietary exogenous hydrophilic emulsifiers from 0 to 0.075% in broiler diets improved the growth rate and feed efficiency of broilers without any deleterious effects on nutrient digestibility, although a corn-soybean meal-based diet had less energy content (3,025 and 3,075 metabolizable energy/kg) for 0-3 weeks and 3-5 weeks, respectively.
Journal of the Korean Society of Marine Environment & Safety
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v.28
no.4
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pp.610-619
/
2022
Hydrogen is emerging as an alternative fuel for eco-friendly ships because it reacts with oxygen to produce electrical energy and only water as a by-product. However, unlike regular fossil fuels, hydrogen has a material with a high risk of explosion due to its low ignition point and high flammability range. In order to safely use hydrogen in ships, it is an essential task to study the flow characteristics of hydrogen leakage and diffusion need to be studied. In this study, a numerical analysis was performed on the effect of leakage, ventilation, etc. on ventilation performance when hydrogen leaks in an enclosed space such as inside a ship. ANSYS CFX ver 18.1, a commercial CFD software, was used for numerical analysis. The leakage rate was changed to 1 q, 2 q, and 3 q at 1 q = 1 g/s, the ventilation rate was changed to 1 Q, 2 Q and 3 Q at 1 Q = 0.91 m/s, and the ventilation method was changed to type I, type II, type III to analyze the ventilation performance was analyzed. As the amount of leakage increased from 1 q to 3 q, the HMF in the storage room was about 2.4 to 3.0 times higher. Furthermore, the amount of ventilation to reduce the risk of explosion should be at least 2 Q, and it was established that type III was the most suitable method for the formation of negative pressure inside the hydrogen tank storage room.
NFT is literally a 'non-fungible token', a digital file that records specific virtual assets on a blockchain. Events such as ownership of the asset and transaction history are recorded on the blockchain through the token transaction, so counterfeiting and falsification are impossible. Therefore, NFT is used as a tool that can uniquely represent a specific virtual asset. The main purpose of this paper is to examine the characteristics of NFT from a records management point of view and to find ways to use them, and focuses on digital records that have the characteristics of assets as digital works. For this purpose, we first examine the basic concept of NFT and the principle of ownership and proof of value as an asset for digital works. In addition, it was confirmed how the advantages of NFT were applied through NFT use cases in various fields, and in particular, areas related to audio-visual records such as art, music, sports, and fashion were focused on. Furthermore, by comparing the characteristics of digital records with those of NFT, factors applicable to electronic records were identified. Finally, the types of digital records that are expected to be effective in the application of NFT were identified, and the possibility of their use and discussion points for introduction in records management are presented.
Lee, Sang Yun;Song, Ki-Il;Kang, Kyung Nam;Ryu, Hee Hwan
Journal of Korean Tunnelling and Underground Space Association
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v.24
no.4
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pp.341-353
/
2022
Pipelines are buried in urban area, and the position (depth and orientation) of buried pipeline should be clearly identified before ground excavation. Although various geophysical methods can be used to detect the buried pipeline, it is not easy to identify the exact information of pipeline due to heterogeneous ground condition. Among various non-destructive geo-exploration methods, ground penetration radar (GPR) can explore the ground subsurface rapidly with relatively low cost compared to other exploration methods. However, the exploration data obtained from GPR requires considerable experiences because interpretation is not intuitive. Recently, researches on automated detection technology for GPR data using deep learning have been conducted. However, the lack of GPR data which is essential for training makes it difficult to build up the reliable detection model. To overcome this problem, we conducted a preliminary study to improve the performance of the detection model using finite difference time domain (FDTD)-based numerical analysis. Firstly, numerical analysis was performed with homogeneous soil media having single permittivity. In case of heterogeneous ground, numerical analysis was performed considering the ground heterogeneity using fractal technique. Secondly, deep learning was carried out using convolutional neural network. Detection Model-A is trained with data set obtained from homogeneous ground. And, detection Model-B is trained with data set obtained from homogeneous ground and heterogeneous ground. As a result, it is found that the detection Model-B which is trained including heterogeneous ground shows better performance than detection Model-A. It indicates the ground heterogeneity should be considered to increase the performance of automated detection model for GPR exploration.
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