• Journal of Bio-Environment Control
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• v.28 no.2
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• pp.143-149
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• 2019

This study was conducted to investigate the graft-taking and growth of grafted cucumber seedlings as affected by light quality and blink cycle of LED modules. Four light quality treatments, namely blue, red, blue+red, white LED and four blink cycle levels of 5s/5s, 7s/3s, 9s/1s and control were provided to investigate the effect of lighting quality and blink cycle on the graft-taking and growth of grafted cucumber seedlings. Photoperiod for the control was 12/12 h. Photosynthetic photon flux, air temperature, and relative humidity for healing were maintained at $100{\mu}mol{\cdot}m^{-2}{\cdot}s^{-1}$, $25^{\circ}C$, and 90%, respectively. There was no significant difference in graft-taking of grafted cucumber seedlings according to light quality except the blue LED with the blink cycle of 5s/5s. Regardless of the blink cycle, there was no significant difference in graft-taking of cucumber seedlings healed under red, blue+red, and white LED modules. These results implied that the effects of light quality and blink cycle on the graft-taking were not significant. Differences in the leaf length, leaf area, and fresh weight of cucumber seedlings healed blue or red LED with the blink cycle of 9s/1s were found to be significant. There was no significant effect of the blink cycle on the growth of cucumber seedlings healed under white LED modules. The prices of white LED are gradually falling due to increased demand. Considering the manufacturing unit price of white LED modules, the cost savings of 10-15% are expected as compared to the conventional blue/red LED modules. Therefore, it was concluded that the use of white LED modules will be economical as an artificial lighting sources for healing of grafted seedlings.

• Journal of the Society of Disaster Information
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• v.16 no.4
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• pp.813-823
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• 2020

Purpose: In order to maximize the stability and productivity of the work through simulation prior to high-risk facilities and high-cost work such as dismantling the facilities inside the reactor, we intend to use digital twin technology that can be closely controlled by simulating the specifications of the actual control equipment. Motion control errors, which can be caused by the time gap between precision control equipment and simulation in applying digital twin technology, can cause hazards such as collisions between hazardous facilities and control equipment. In order to eliminate and control these situations, prior research is needed. Method: Unity 3D is currently the most popular engine used to develop simulations. However, there are control errors that can be caused by time correction within Unity 3D engines. The error is expected in many environments and may vary depending on the development environment, such as system specifications. To demonstrate this, we develop crash simulations using Unity 3D engines, which conduct collision experiments under various conditions, organize and analyze the resulting results, and derive tolerances for precision control equipment based on them. Result: In experiments with collision experiment simulation, the time correction in 1/1000 seconds of an engine internal function call results in a unit-hour distance error in the movement control of the collision objects and the distance error is proportional to the velocity of the collision. Conclusion: Remote decomposition simulators using digital twin technology are considered to require limitations of the speed of movement according to the required precision of the precision control devices in the hardware and software environment and manual control. In addition, the size of modeling data such as system development environment, hardware specifications and simulations imitated control equipment and facilities must also be taken into account, available and acceptable errors of operational control equipment and the speed required of work.

• Knowledge Management Research
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• v.22 no.2
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• pp.119-144
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• 2021

Recently, as competition in the market evolves from the competition among companies to the competition among their supply chains, companies are struggling to enhance their supply chain management (hereinafter SCM). In particular, as blockchain technology with various technical advantages is combined with SCM, a lot of domestic manufacturing and distribution companies are considering the adoption of blockchain-oriented SCM (BOSCM) services today. Thus, it is an important academic topic to examine the factors affecting the use of blockchain-oriented SCM. However, most prior studies on blockchain and SCMs have designed their research models based on Technology Acceptance Model (TAM) or the Unified Theory of Acceptance and Use of Technology (UTAUT), which are suitable for explaining individual's acceptance of information technology rather than companies'. Under this background, this study presents a novel model of blockchain-oriented SCM acceptance model based on the Technology-Organization-Environment (TOE) framework to consider companies as the unit of analysis. In addition, Value-based Adoption Model (VAM) is applied to the research model in order to consider the benefits and the sacrifices caused by a new information system comprehensively. To validate the proposed research model, a survey of 126 companies were collected. Among them, by applying PLS-SEM (Partial Least Squares Structural Equation Modeling) with data of 122 companies, the research model was verified. As a result, 'business innovation', 'tracking and tracing', 'security enhancement' and 'cost' from technology viewpoint are found to significantly affect 'perceived value', which in turn affects 'intention to use blockchain-oriented SCM'. Also, 'organization readiness' is found to affect 'intention to use' with statistical significance. However, it is found that 'complexity' and 'regulation environment' have little impact on 'perceived value' and 'intention to use', respectively. It is expected that the findings of this study contribute to preparing practical and policy alternatives for facilitating blockchain-oriented SCM adoption in Korean firms.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.33 no.6
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• pp.265-274
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• 2021

Outlier detection research in ocean data has traditionally been performed using statistical and distance-based machine learning algorithms. Recently, AI-based methods have received a lot of attention and so-called supervised learning methods that require classification information for data are mainly used. This supervised learning method requires a lot of time and costs because classification information (label) must be manually designated for all data required for learning. In this study, an autoencoder based on unsupervised learning was applied as an outlier detection to overcome this problem. For the experiment, two experiments were designed: one is univariate learning, in which only SST data was used among the observation data of Deokjeok Island and the other is multivariate learning, in which SST, air temperature, wind direction, wind speed, air pressure, and humidity were used. Period of data is 25 years from 1996 to 2020, and a pre-processing considering the characteristics of ocean data was applied to the data. An outlier detection of actual SST data was tried with a learned univariate and multivariate autoencoder. We tried to detect outliers in real SST data using trained univariate and multivariate autoencoders. To compare model performance, various outlier detection methods were applied to synthetic data with artificially inserted errors. As a result of quantitatively evaluating the performance of these methods, the multivariate/univariate accuracy was about 96%/91%, respectively, indicating that the multivariate autoencoder had better outlier detection performance. Outlier detection using an unsupervised learning-based autoencoder is expected to be used in various ways in that it can reduce subjective classification errors and cost and time required for data labeling.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.42 no.6
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• pp.853-860
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• 2022

The purpose of this study is to suggest an improvement plan for the calculation method of the engineer standard wage rate (ESWR) and to compute a reasonable ESWR. To this end, an adequacy review of theESWR calculation criteria was conducted along with an extensive engineering industry survey. The survey results were analyzed using an effective response sample of 748 companies out of 1,000 survey samples extracted by stratifying the 5,879 survey population. The main results were as follows. ①When calculating the engineering service fee, the prime contractor's engineer wage is suitable for the ESWR. The ESWR can be estimated by the formula 'average wage÷[1-proportion of subcontract orders×(1-subcontract rate)].' ② The field survey showed that the number of monthly working days was 20.35-20.54 days at 99 % confidence interval, which was significantly different from the current standard (22 days). In addition, as a result of a legal review of the ESWR criteria, it was found that the number of working days should be calculated in accordance with the Labor Standards Act after 2022. ③ Applying government guidelines, the time difference between the wage survey and the ESWR application can be corrected by the past ESWR increase rate for a specific period. ④ Using modeling based on the analysis above, the current ESWR was 13.5-14.5 % lower than the appropriate level. A lower ESWR was driven by the non-reflection of subcontract structure (4.1 %), overestimation of monthly work days (6.8-7.8 %), and application of past wage (2.6 %). The proposed model is expected to be widely used in policy making, as it can provide a useful framework for calculating the standard wage rate in similar industries as well as calculating appropriate engineering fees.

• Journal of the Korea Institute of Building Construction
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• v.22 no.5
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• pp.473-483
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• 2022

BIM(Building Information Modeling) is a technology that can manage information throughout the entire life cycle of the construction industry and serves as a platform for improving productivity and integrating the entire construction industry. Currently, BIM is actively applied in developed countries, and its use at various overseas construction sites is increasing This is unclear. due to air shortening and budget savings. However, there is still a lack of institutional basis and technical limitations in the domestic construction sector, which have led to the lack of utilization of BIM. Various activation measures and institutional frameworks will need to be established for the early establishment of these productive BIMs in Korea. Therefore, as part of the research for the domestic settlement and revitalization of BIM, this study derived a number of key factors necessary for the development of the construction industry through brainstorming and expert surveys using AHP techniques and analyzed the relative importance of each factor. In addition, prior surveys by a group of experts resulted in 1, 3 items in level, 2, 9 items in level, and 3, 27 items in level, and priorities analysis was performed through pairwise comparisons. As a result of the AHP analysis, it was found that the relative importance weight of policy aspects was highest in level 1, and the policy factors in level 2 and the cost-based and incentive system introduction factors were considered most important in level 3. These findings show that the importance of the policy guidance or institutions underlying the activation of BIM rather than research and development or corporate innovation is relatively high, and that the preparation of policy plans by public institutions should be the first priority. Therefore, it is considered that the development of a policy system or guideline must be prioritized before it can be advanced to the next activation stage. The use of BIM technologies will not only contribute to improving the productivity of the construction industry, but also to the overall development of the industry and the growth of the construction industry. It is expected that the results of this study can provide as useful information when establishing policies for activating BIM in central government, relevant local governments, and related public institutions.

• Journal of Intelligence and Information Systems
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• v.28 no.4
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• pp.41-59
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• 2022

The timely procurement of military supplies is essential to maintain the military's operational capabilities, and contract work is the first step toward timely procurement. In addition, rapid signing of a contract enables consumers to set a leisurely delivery date and increases the possibility of budget execution, so it is essential to improve the contract process to prevent early execution of the budget and transfer or disuse. Recently, research using big data has been actively conducted in various fields, and process analysis using big data and process mining, an improvement technique, are also widely used in the private sector. However, the analysis of contract work in the military is limited to the level of individual analysis such as identifying the cause of each problem case of budget transfer and disuse contracts using the experience and fragmentary information of the person in charge. In order to improve the contract process, this study analyzed using the process mining technique with data on a total of 560 contract tasks directly contracted by the Department of Finance of the Air Force Logistics Command for about one year from November 2019. Process maps were derived by synthesizing distributed data, and process flow, execution time analysis, bottleneck analysis, and additional detailed analysis were conducted. As a result of the analysis, it was found that review/modification occurred repeatedly after request in a number of contracts. Repeated reviews/modifications have a significant impact on the delay in the number of days to complete the cost calculation, which has also been clearly revealed through bottleneck visualization. Review/modification occurs in more than 60% of the top 5 departments with many contract requests, and it usually occurs in the first half of the year when requests are concentrated, which means that a thorough review is required before requesting contracts from the required departments. In addition, the contract work of the Department of Finance was carried out in accordance with the procedures according to laws and regulations, but it was found that it was necessary to adjust the order of some tasks. This study is the first case of using process mining for the analysis of contract work in the military. Based on this, if further research is conducted to apply process mining to various tasks in the military, it is expected that the efficiency of various tasks can be derived.

• 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.

• Clean Technology
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• v.28 no.2
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• pp.131-137
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• 2022

The semiconductor process currently emits various by-products and unused gases. Emissions containing pollutants are generally classified into categories such as organic, acid, alkali, thermal, and cabinet exhaust. They are discharged after treatment in an atmospheric prevention facility suitable for each exhaust type. The main components of organic exhaust are volatile organic compounds (VOC), which is a generic term for oxygen-containing hydrocarbons, sulfur-containing hydrocarbons, and volatile hydrocarbons, while the main components of alkali exhaust include ammonia and tetramethylammonium hydroxide. The purpose of this study was to determine the combustion characteristics and analyze the NO_X reduction rate by maintaining a direct combustion and temperature to process organic and alkaline exhaust gases simultaneously. Acetone, isopropyl alcohol (IPA), and propylene glycol methyl ether acetate (PGMEA) were used as VOCs and ammonia was used as an alkali exhaust material. Independent and VOC-ammonia mixture combustion tests were conducted for each material. The combustion tests for the VOCs confirmed that complete combustion occurred at an equivalence ratio of 1.4. In the ammonia combustion test, the NO_X concentration decreased at a lower equivalence ratio. In the co-combustion of VOC and ammonia, NO was dominant in the NO_X emission while NO₂ was detected at approximately 10 ppm. Overall, the concentration of nitrogen oxide decreased due to the activation of the oxidation reaction as the reaction temperature increased. On the other hand, the concentration of carbon dioxide increased. Flameless combustion with an electric heat source achieved successful combustion of VOC and ammonia. This technology is expected to have advantages in cost and compactness compared to existing organic and alkaline treatment systems applied separately.

• Journal of the Korean Society of Marine Environment & Safety
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• v.28 no.7
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• pp.1209-1215
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• 2022

The selective catalytic reduction (SCR) is known as a very efficient method to reduce nitrogen oxides (NOx) and the catalyst performs reduction from nitrogen oxides (NOx) to nitrogen (N₂) and water vapor (H2O). The catalyst, which is one of the factors determining the performance of the nitrogen oxide (NOx) ruduction method, is known to increase catalyst efficiency as cell density increases. In this study, the reduction characteristics of nitrogen oxides (NOx) under various engine loads investigated. A 100CPSI(60Cell) catalysts was studied through a laboratory-sized simulating device that can simulate the exhaust gas conditions from the power generation engine installed in the training ship SEGERO. The effect of 100CPSI(60Cell) cell density was compared with that of 25.8CPSI(30Cell) cell density that already had NOx reduction data from the SCR manufacturing. The experimental catalysts were honeycomb type and its compositions and materials of V₂O₅-WO₃-TiO₂ were retained, with only change on cell density. As a result, the NOx concentration reduction rate from 100CPSI(60Cell) catalyst was 88.5%, and IMO specific NOx emission was 0.99g/kwh satisfying the IMO Tier III NOx emission requirement. The NOx concentration reduction rate from 25.8CPSI(30Cell) was 78%, and IMO specific NOx emission was 2.00g/kwh. Comparing the NOx concentration reduction rate and emission of 100CPSI(60Cell) and 25.8CPSI(30Cell) catalysts, notably, the NOx concentration reduction rate of 100CPSI(60Cell) catalyst was 10.5% higher and its IMO specific NOx emission was about twice less than that of the 25.8CPSI(30Cell) catalysts. Therefore, an efficient NOx reduction effect can be expected by increasing the cell density of catalysts. In other words, effects to production cost reduction, efficient arrangement of engine room and cargo space can be estimated from the reduced catalyst volume.