• Korean Journal of Construction Engineering and Management
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• v.19 no.1
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• pp.80-89
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• 2018

World Bank projects enable Korean engineering firms to enter new markets and diversify their portfolio. These firms need to understand the critical factors for bidding success in such projects. The World Bank publishes as open records all their bidding history data in their open database. This provides an opportunity to identify empirically the factors that determine which firms on chosen. This research collected relevant bid data, focusing on Indonesia, to perform a logistic regression with the goal of statistically identifying significant factors that result in bidding success. Results showed that work experience, being included in a consortium, and having a local partner positively affected winning a bid. On the other hand, having a local competitor of the recipient country negatively impacts the chances of attaining a bid. Commensurately, Korean engineering firms need to increase their work experience in internationally recognized projects, and include a local partner as a joint venture partner to increase their chances, while refrain from conventional projects that can be performed by local engineering firms.

• Korean Journal of Materials Research
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• v.28 no.12
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• pp.732-737
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• 2018

We develop a purification process of $Hg_2Br_2$ raw powders using a physical vapor transport(PVT) process, which is essential for the fabrication of a high performance acousto-optic tunable filter(AOTF) module. Specifically, we characterize and compare three $Hg_2Br_2$ powders: $Hg_2Br_2$ raw powder, $Hg_2Br_2$ powder purified under pumping conditions, and $Hg_2Br_2$ powder purified under vacuum sealing. Before and after purification, we characterize the powder samples through X-ray diffraction and X-ray photoelectron spectroscopy. The corresponding results indicate that physical properties of the $Hg_2Br_2$ compound are not damaged even after the purification process. The impurities and concentration in the purified $Hg_2Br_2$ powder are evaluated by inductively coupled plasma-mass spectroscopy. Notably, compared to the sample purified under pumping conditions, the purification process under vacuum sealing results in a higher purity $Hg_2Br_2$ (99.999 %). In addition, when the second vacuum sealing purification process is performed, the remaining impurities are almost removed, giving rise to $Hg_2Br_2$ with ultra-high purity. This high purification process might be possible due to independent control of impurities and $Hg_2Br_2$ materials under the optimized vacuum sealing. Preparation of such a highly purified $Hg_2Br_2$ materials will pave a promising way toward a high-quality $Hg_2Br_2$ single crystal and then high performance AOTF modules.

• Clean Technology
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• v.27 no.2
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• pp.115-123
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• 2021

This study demonstrates a new method for the synthesis of organic-inorganic hybrid particles composed of an inorganic silica shell and organic core particles. The organic core particles are prepared with a uniform size using droplet-based microfluidic technology. In the process of preparing the organic core particles, uniform droplets are generated by independently controlling the flow rates of the dispersed phase containing photocurable resins and the continuous phase. After the generation of droplets in a microfluidic device, the droplets are photo-polymerized as particles by ultraviolet irradiation at the ends of microfluidic channels. The core particle is coated with a nano complex composed of polyallylamine hydrochloride (PAH) and phosphate ion (Pi) through strong non-covalent interactions such as hydrogen bonding and electrostatic interaction under optimized pH conditions. The polyamine nano complex rapidly induces the condensation reaction of silicic acid through the arranged amine groups of the main chain of PAH. Therefore, this method enabled the preparation of organic-inorganic hybrid particles coated with inorganic silica nanoparticles on the organic core. Finally, we demonstrated the synthesis of organic-inorganic hybrid particles in a short time under ambient and environmentally friendly conditions, and this is applicable to the production of organic-inorganic hybrid particles having various sizes and shapes.

• Journal of Korean Society on Water Environment
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• v.27 no.4
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• pp.467-474
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• 2011

In an effort to investigate water pollution characteristics of Juam lake, water samples were collected from three sites (Sites A, B, and C) of Oenam stream which is a typical tributary of rural watershed in the lake and analyzed for N concentration and the corresponding isotope ratio (${\delta}^{15}N$) of ${NO_3}^-$. Concentrations of ${NO_3}^-$ were not dramatically different among the sites; $0.8{\pm}0.2mgNL^{-1}$ (range: $0.0{\sim}4.3mgNL^{-1}$) for Site A, $1.1{\pm}0.2mgNL^{-1}$ ($0.0{\sim}4.3mgNL^{-1}$) for Site B, and $1.1{\pm}0.1mgNL^{-1}$ ($0.1{\sim}2.6mgNL^{-1}$) for Site C. Meanwhile, ${\delta}^{15}N$ tended to decrease with river flow; it was highest for Site A ($45.5{\pm}5.3$‰) followed by Site B ($19.7{\pm}2.0$‰) and Site C ($8.7{\pm}1.5$‰). Such high ${\delta}^{15}N$ values of ${NO_3}^-$ in Site A suggested that ${NO_3}^-$ derived from livestock feedlot (specifically livestock excrete of which ${\delta}^{15}N$ is higher than 10‰) is the predominant pollution sources despite mountainous area occupied the most of land-use in the watershed. Using the two-sources isotope mixing model, it was estimated that the contribution of cropping activities (i.e. fertilization) became greater in down-stream area (Sites B and C) due to the higher agricultural land-use than the up-stream area (Site A). Particularly, during the active cropping season, the low contribution of organic pollution sources indicated that domestic sewage was not the predominant pollution source. Therefore, it was suggested that agricultural sources such as livestock farming and cropping rather than mountainous and residential are the dominant sources of water pollution in the study area. These results could be effectively utilized in elucidating water pollution sources in rural areas and selecting water management practices.

• The Journal of the Acoustical Society of Korea
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• v.41 no.3
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• pp.278-286
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• 2022

In this study, a 33-mode Free-Flooded Ring (FFR) transducer was designed to apply piezoelectric single crystal PIN-PMN-PT, which has high piezoelectric constants and electromechanical coupling coefficient. To ensure low-frequency high transmitting sensitivity characteristics with a small size of FFR transducer, the commercial FFR transducer based on piezoelectric ceramics was compared. To develop the FFR transducer with broadband characteristics, a piezoelectric segmented ring structure inserted with inactive elements was applied. The oil-filled structure was applied to minimize the change of acoustic characteristics of the ring transducer. It was verified that the transmitting voltage response, underwater impedance, and beam pattern matched the finite element numerical simulation results well through an acoustic test. The difference in the transmitting voltage response between the measured and the simulated results is about 1.3 dB in cavity mode and about 0.3 dB in radial mode. The fabricated FFR transducer had a higher transmitting voltage response compared to the commercial transducer, but the diameter was reduced by about 17 %. From this study, it was confirmed that the feasibility of a single crystal-applied FFR transducer with compact size and high-power characteristics. The effectiveness of the performance prediction by simulation was also confirmed.

• Journal of Adhesion and Interface
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• v.24 no.1
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• pp.26-35
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• 2023

Generally, solvent-type coatings generate a large amount of volatile organic chemicals(VOC), which are carcinogenic substances, in the manufacturing process, and their use is regulated due to environmental problems. There is also the problem of resource depletion due to limited fossil fuels. Therefore, in this study, UV-curable urethane acrylate oligomers were synthesized with different contents of isosorbide, which is a biomass material, and proceeded to evaluate the physical properties of coatings. As the isosorbide contents increased, the viscosity, glass transition temperature, tensile strength, stain resistance, and pencil hardness increased, but elongation and flexibility decreased, and BOI-3 showed the best adhesion. The isosorbide content of the oligomer fixed at 20%, UV-curable urethane acrylate oligomer was synthesized according to the content ratio of polycaprolactone diol(PCL) and Ecoprol H1000(Ecoprol). As the PCL/Ecoprol content ratio increased, the glass transition temperature, elongation, and flexibility increased, but the tensile strength and pencil hardness decreased. It was confirmed that the adhesion and stain resistance increased by improving the surface bonding strength of PCL. All films of oligomers synthesized were transparent without discoloration.

• Applied Chemistry for Engineering
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• v.34 no.4
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• pp.404-411
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• 2023

For the direct reforming of biogas, a three-phase gliding arc plasma reformer was designed to expand the plasma discharge region, and the operation conditions of the plasma reformer, such as the S/C ratio, the gas flow rate, and the plasma input power, were optimized. The H₂ production efficiency is increased at a lower specific plasma input energy density, but byproducts such as C_XH_Y and carbon soot are generated along with the increase in H₂ production efficiency. The formation of byproducts is decreased at higher specific plasma input energy densities and S/C ratios. The optimized operation conditions are 5.5 ~ 6.0 kJ/L for the specific plasma input energy density and 3 for the S/C ratio, considering the conversion efficiency, H₂ production, and byproduct formation. It is expected that the H₂ production efficiency will improve with the decrease in fuel consumption in biogas burners because the heat generated from plasma discharge heats up the feed gas to over 500 ℃.

• Journal of Intelligence and Information Systems
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• v.27 no.3
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• pp.57-73
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• 2021

Maintenance and prevention of failure through anomaly detection of ICT infrastructure is becoming important. System monitoring data is multidimensional time series data. When we deal with multidimensional time series data, we have difficulty in considering both characteristics of multidimensional data and characteristics of time series data. When dealing with multidimensional data, correlation between variables should be considered. Existing methods such as probability and linear base, distance base, etc. are degraded due to limitations called the curse of dimensions. In addition, time series data is preprocessed by applying sliding window technique and time series decomposition for self-correlation analysis. These techniques are the cause of increasing the dimension of data, so it is necessary to supplement them. The anomaly detection field is an old research field, and statistical methods and regression analysis were used in the early days. Currently, there are active studies to apply machine learning and artificial neural network technology to this field. Statistically based methods are difficult to apply when data is non-homogeneous, and do not detect local outliers well. The regression analysis method compares the predictive value and the actual value after learning the regression formula based on the parametric statistics and it detects abnormality. Anomaly detection using regression analysis has the disadvantage that the performance is lowered when the model is not solid and the noise or outliers of the data are included. There is a restriction that learning data with noise or outliers should be used. The autoencoder using artificial neural networks is learned to output as similar as possible to input data. It has many advantages compared to existing probability and linear model, cluster analysis, and map learning. It can be applied to data that does not satisfy probability distribution or linear assumption. In addition, it is possible to learn non-mapping without label data for teaching. However, there is a limitation of local outlier identification of multidimensional data in anomaly detection, and there is a problem that the dimension of data is greatly increased due to the characteristics of time series data. In this study, we propose a CMAE (Conditional Multimodal Autoencoder) that enhances the performance of anomaly detection by considering local outliers and time series characteristics. First, we applied Multimodal Autoencoder (MAE) to improve the limitations of local outlier identification of multidimensional data. Multimodals are commonly used to learn different types of inputs, such as voice and image. The different modal shares the bottleneck effect of Autoencoder and it learns correlation. In addition, CAE (Conditional Autoencoder) was used to learn the characteristics of time series data effectively without increasing the dimension of data. In general, conditional input mainly uses category variables, but in this study, time was used as a condition to learn periodicity. The CMAE model proposed in this paper was verified by comparing with the Unimodal Autoencoder (UAE) and Multi-modal Autoencoder (MAE). The restoration performance of Autoencoder for 41 variables was confirmed in the proposed model and the comparison model. The restoration performance is different by variables, and the restoration is normally well operated because the loss value is small for Memory, Disk, and Network modals in all three Autoencoder models. The process modal did not show a significant difference in all three models, and the CPU modal showed excellent performance in CMAE. ROC curve was prepared for the evaluation of anomaly detection performance in the proposed model and the comparison model, and AUC, accuracy, precision, recall, and F1-score were compared. In all indicators, the performance was shown in the order of CMAE, MAE, and AE. Especially, the reproduction rate was 0.9828 for CMAE, which can be confirmed to detect almost most of the abnormalities. The accuracy of the model was also improved and 87.12%, and the F1-score was 0.8883, which is considered to be suitable for anomaly detection. In practical aspect, the proposed model has an additional advantage in addition to performance improvement. The use of techniques such as time series decomposition and sliding windows has the disadvantage of managing unnecessary procedures; and their dimensional increase can cause a decrease in the computational speed in inference.The proposed model has characteristics that are easy to apply to practical tasks such as inference speed and model management.