• Journal of the Korean Geotechnical Society
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• v.23 no.5
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• pp.111-129
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• 2007

The standard construction manual of the SDA(Separated Doughnut Auger) piling method was proposed so that the resisting capacity of the augered piles could work effectively. 405 dynamic pile load tests and 30 static pile load tests were performed for 265 test piles, which were installed by the SDA piling method in 33 sites in Korea. The results of the pile load tests showed that the end bearing capacity of the SDA augered piles depended on the property of various soil stratums and did not agree with ones estimated by the existing formula based on several standard design codes. On the basis of the pile load test results, four formulas were presented according to bearing stratums to estimate quantitatively the unit end bearing capacity of the SDA augered piles. The formulas for the unit end bearing capacity of piles on soils or weathered rocks were related to N-value given by SPT(Standard Penetration Test), while the unit end bearing capacity on bedrock was suggested to be more than 1500 $tf/m^2$. The presented formulas were compared with the existing formulas, which were presented by several standard design codes to design the augered piles. In order to use correctly the presented formulas, the quality of Standard Penetration Test should be controlled precisely. Also it is desirable to choose a pilot construction site, where both dynamic and static pile load tests are performed.

• Applied Chemistry for Engineering
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• v.25 no.2
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• pp.121-133
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• 2014

Block copolymers including ABA triblock architectures are useful as thermoplastic elastomers and toughened plastics depending on the relative glassy and rubbery content. These materials can be blended with other polymers and utilized as additives, toughening agents, and compatibilizers. Most of commercially available block copolymers are derived from petroleum. Renewable alternatives are attractive considering the finite supply of fossil resources on earth and the overall economic and environmental expenses involved in the recovery and use of oil. Furthermore, tomorrow's sustainable materials are demanding the design and implementation with programmed end-of-life. The present review focuses on the preparation and evaluation of new classes of renewable ABA triblock copolymers and also emphasizes on the use of carbohydrate-derived poly(lactide) or plant-based poly(olefins) having a high glass transition temperature and/or high melting temperature for the hard phase in addition to the use of bio-based amorphous hydrocarbon polymers with a low glass transition temperature for the soft components. The combination of multiple controlled polymerizations has proven to be a powerful approach. Precision-controlled synthesis of these hybrid macromolecules has led to the development of new elastomers and tough plastics offering renewability, biodegradability, and high performance.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.5
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• pp.36-46
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• 2019

The number of hosts connected to the Internet has increased dramatically, introducing the Domain Name System(DNS) in 1984. DNS is now an important key point for all users of the Internet by allowing them to use a convenient character address without memorizing a series of numbers of complex IP address. However, relative to the importance of DNS, there still exist many problems such as the authorization allocation issue, the disputes over public registration, security vulnerability such as DNS cache poisoning, DNS spoofing, man-in-the-middle attack, DNS amplification attack, and the need for many domain names in the age of hyper-connected networks. In this paper, to effectively improve these problems of existing DNS, we proposed a method of implementing DNS using distributed ledger technology, blockchain, and implemented using a Ethereum-based platform. In addition, the qualitative analysis performance comparative evaluation of the existing domain name registration and domain name server was conducted, and conducted security assessments on the proposed system to improve security problem of existing DNS. In conclusion, it was shown that DNS services could be provided high security and high efficiently using blockchain.

• Journal of the Korean Society of Marine Environment & Safety
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• v.27 no.1
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• pp.53-59
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• 2021

The marine transport industry generally applies new technologies later than other transport industries, such as airways and railways. Vessels require efficient operation, and their performance and lifespan depend on the level of maintenance and management. Many studies have shown that corrective maintenance (CM) and time-based maintenance (TBM) have restrictions with respect to enabling efficient maintenance of workload and cost to improve operational efficiency. Predictive maintenance (PdM) is an advanced technology that allows monitoring the condition and performance of a target machine to predict its time of failure and helps maintain the key machinery in optimal working conditions at all times. This study presents the development of a marine predictive maintenance (MPdM; maritime predictive maintenance) method based on applying PdM to the marine environment. The MPdM scheme is designed by considering the special environment of the marine transport industry and the extreme marine conditions. Further, results of the study elaborates upon the concept of MPdM and its necessity to advancing marine transportation in the future.

• Journal of Advanced Marine Engineering and Technology
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• v.39 no.6
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• pp.633-641
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• 2015

Several complex processes that are employed in industries, such as shipping, power plants, and the petrochemical industry, involve time-varying behavior as well as strong nonlinear behavior during operation. The fixed-parameter proportional-integral-derivative (PID) controllers have difficulty in dealing with control problems that occur in such processes. In this paper, we propose a method of designing a nonlinear PID controller for industrial processes that exhibit a large number of nonlinearities and time-varying behavior. The gains of the nonlinear PID controller are characterized by a simple nonlinear function of the error and/or error rate depending on the process set-point and output. We tune the user-defined parameters using a genetic algorithm by minimizing the integral of time absolute error (ITAE) index. We verify the effectiveness of the proposed method by performing a comparison of the proposed method and two other nonlinear and adaptive methods that are employed for reference tracking, disturbance-rejection performances, and robustness to parameter changes on a continuously stirred tank reactor.

• Journal of the Institute of Electronics and Information Engineers
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• v.52 no.7
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• pp.135-142
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• 2015

Human-powered self-generating devices have been attractive with its operation characteristic independent from outer environment such as weather condition and wind speed. However, conventional self-generators have low electric power output due to their weakly-coupled electromagnetic structure. More importantly, rotary crank motion which is usually adopted by conventional self-generator to generate electricity requires specific skeletal muscles to maintain large torque circular motion and consequently, causes fatigue on those muscles before it can generate enough amount of electricity for any practical application. Without improvement in electric power output and usability, the human-powered self-generator could not be used in everyday life. This study aims to develop a human-powered self-generator which realized a strong electromagnetic coupling in a closed-loop tubular structure (hula-hoop shape) for easy and steady long-term driving as well as larger electric output. The performance and usability of the developed human-powered generator is verified through experimental comparison with a commercial one. Additionally, human workload which is a key element of a human-powered generator but not often considered elsewhere, is estimated based on metabolic energy expenditure measured respiratory gas analyzer. Further study will focus on output and portability enhancement, which can contribute to the continuous power supply of mobile equipments.

• Korean Journal of Clinical Laboratory Science
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• v.54 no.2
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• pp.79-94
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• 2022

Due to the highly contagious nature and severity of the respiratory diseases caused by COVID-19, economical and accurate tests are required to better monitor and prevent the spread of this contagion. As the structural and molecular properties of SARS-CoV-2 were being revealed during the early stage of the COVID-19 pandemic, many manufacturers of COVID-19 diagnostic kits actively invested in the design, development, validation, verification, and implementation of diagnostic tests. Currently, diagnostic tests for SARS-CoV-2 are the most widely used and validated techniques for rapid antigen, and immuno-serological assays for specific IgG and IgM antibody tests and molecular diagnostic tests. Molecular diagnostic assays are the gold standard for direct detection of viral RNA in individuals suspected to be infected with SARS-CoV-2. Antibody-based serological tests are indirect tests applied to determine COVID-19 prevalence in the community and identify individuals who have obtained immunity. In the future, it is necessary to explore technical problems encountered in the early stages of global or regional outbreaks of pandemics and provide future directions for better diagnostic tests. This article evaluates the commercially available and FDA-approved molecular and immunological diagnostic assays and analyzes their performance characteristics.

• Journal of Korean Society of Disaster and Security
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• v.14 no.4
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• pp.17-27
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• 2021

Streamflow prediction is a very vital disaster mitigation approach for effective flood management and water resources planning. Lately, torrential rainfall caused by climate change has been reported to have increased globally, thereby causing enormous infrastructural loss, properties and lives. This study evaluates the contribution of rainfall to streamflow prediction in normal and peak rainfall scenarios, typical of the recent flood at Piney Resort in Vernon, Hickman County, Tennessee, United States. Daily streamflow, water level, and rainfall data for 20 years (2000-2019) from two USGS gage stations (03602500 upstream and 03599500 downstream) of the Piney River watershed were obtained, preprocesssed and fitted with Long short term memory (LSTM) model. Tensorflow and Keras machine learning frameworks were used with Python to predict streamflow values with a sequence size of 14 days, to determine whether the model could have predicted the flooding event in August 21, 2021. Model skill analysis showed that LSTM model with full data (water level, streamflow and rainfall) performed better than the Naive Model except some rainfall models, indicating that only rainfall is insufficient for streamflow prediction. The final LSTM model recorded optimal NSE and RMSE values of 0.68 and 13.84 m³/s and predicted peak flow with the lowest prediction error of 11.6%, indicating that the final model could have predicted the flood on August 24, 2021 given a peak rainfall scenario. Adequate knowledge of rainfall patterns will guide hydrologists and disaster prevention managers in designing efficient early warning systems and policies aimed at mitigating flood risks.