• Resources Recycling
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• v.28 no.1
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• pp.47-54
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• 2019

In this study, the wastes were used as fuels for direct reduction iron (DRI) production to reduce production cost and recycle the wastes. We examined the effects of wastes on the reduction behavior of DRI manufacture and the possibility of using wastes as auxiliary fuels. The proximate and Ultimate analysis were carried out to confirm the properties of wastes as fuels, and high-quality reduced irons were fabricated by using the waste as an auxiliary fuel. The metallization of reduced irons increased as the calorific value increase of auxiliary fuel. Especially, the reduced irons fabricated from the waste tires and vinyl plastics which had high heat energy and volatile matters showed higher metallization than the others. The high calorific value and volatility of waste were significant properties as fuel. The high quality DRI could be fabricated with wastes as auxiliary fuels through optimization of reaction conditions.

• Journal of the HCI Society of Korea
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• v.14 no.2
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• pp.49-60
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• 2019

With the appearance of self-driving cars and electric cars, the automobile industry is rapidly changing. In the midst of these changes, HMI studies are becoming more important as to how the driver obtains safety and convenience with controlling the vehicle. This study sought to understand how automobile manufacturers understand the driving situation, and how they define and limit driver interaction. For this, prior studies about HMI were reviewed and 15 participants performed an on-road study to drive vehicles from five manufacturers with using their interfaces. The results of the study confirmed that buttons and switches that are easily controlled by the user while driving were different from manufacturer to manufacturer. And there are some buttons that are more intensively controlled and others that are difficult to control while driving. It was able to derive 'selection and concentration' from Audi's vehicle, 'optimization of the driving ' from BMW's, 'simple and minimize' from Benz's vehicle, 'remove the manual distraction' from the vehicle of Lexus, and 'visual stability' from KIA's vehicle as the distinctive keywords for the HMI. This shows that each manufacturer has a different definition and interpretation of the driver's driving control area. This study has a distinct value in that it has identified the characteristics of vehicle-specific HMI in actual driving conditions, which is not apparent in appearance. It is expected that this research approach can be useful to see differences in interaction through actual driving despite changes in driving environment such as vehicle platooning and self-driving technology.

• Microbiology and Biotechnology Letters
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• v.47 no.3
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• pp.390-400
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• 2019

In this study, strains isolated from soil samples collected from Busan, Changwon, and Jeju Island were examined to verify their abilities of phosphate solubilization and nitrogen fixation, production of indole-3-acetic acid (IAA), siderophore, and 1-aminocylopropane-1-carboxylyic acid (ACC) deaminase in order to select strains that promote plant growth and play a role in biocontrol of pests or pathogens. According to the results of this study, most of the isolated strains were found to have ability of phosphate solubilization, nitrogen fixation, IAA production, siderophore production, and production of ACC deaminase. These isolated strains might help plant growth by directly improving absorption of nutrients essential for phosphate solubilization and nitrogen fixation. In addition, they can promote plant growth and control resistance to plant diseases through extracellular enzyme activity and antifungal activity. In addition, most of the selected strains were found to survive in various environmental conditions such as temperature, salinity, and pH. Therefore, Pseudomonas plecoglossicida ANG14, Pseudarthrobacter equi ANG28, Beijerinckia fluminensis ANG34, and Acinetobacter calcoaceticus ANG35 were finally selected through a comparative advantage analysis to suggest their potential as novel biological agents. Further studies are necessary in order to prove their efficacy as novel biological agents through formulation and optimization of effective microorganisms, their preservation period, and crop cultivation tests.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.5
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• pp.468-476
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• 2019

This paper presents the means of improving the strength of LTV's FRP structure for resolve and prevent quality problems. LTV secures enough kerb weight by applying FRP materials at hood and rear van assembly. However, because of FRP's inherent limitations, many initial quality problems such as crack at connections have occurred. Moreover, hood assy' is concerned about fall of endurance, because hood assy' have operated in abnormal condition. Therefore, this study executes lamination structure optimizations of FRP structure for improving bending strength. As a results, hood and rear van's bending strength at connections is improved 8.1 times and 1.5 times, respectively. Also hood assy's plate secures endurance life and improve 1.7 times of critical load about abnormal operating conditions through 1.4 times improvement of bending strength.

• Korean Chemical Engineering Research
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• v.59 no.2
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• pp.191-199
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• 2021

A distillation column, which is a main facility of the chemical process, separates the desired product from a mixture by using the difference of boiling points. The distillation process requires the optimization and the prediction of operation because it consumes much energy. The target process of this study is difficult to operate efficiently because the composition of feed flow is not steady according to the supplier. To deal with this problem, we could develop a data-driven model to predict operating conditions. However, data preprocessing is essential to improve the predictive performance of the model because the raw data contains outlier and noise. In this study, after optimizing the predictive model based long-short term memory (LSTM) and Random forest (RF), we used a low-pass filter and one-class support vector machine for data preprocessing and compared predictive performance according to the method and range of the preprocessing. The performance of the predictive model and the effect of the preprocessing is compared by using R2 and RMSE. In the case of LSTM, R2 increased from 0.791 to 0.977 by 23.5%, and RMSE decreased from 0.132 to 0.029 by 78.0%. In the case of RF, R2 increased from 0.767 to 0.938 by 22.3%, and RMSE decreased from 0.140 to 0.050 by 64.3%.

• Korean Journal of Food Science and Technology
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• v.53 no.2
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• pp.174-180
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• 2021

The optimal recipe for manufacturing composite honey-based herbal pills mainly comprising Rubus coreanus powder (RCP), black mulberry powder (BMP), and vitamin C was investigated. Honey-based herbal pills were prepared by mixing these powders, binding them with honey, and then forming a round shape. The experiment was designed based on the D-optimal mixture design, which included 12 experimental points with one replicate for three independent variables as follows: RCP (10~35%), BMP (10~35%), and vitamin C (5~10%). In addition, the dependent variables (total phenolic and flavonoid content and antioxidant activity) were measured and used to optimize the manufacturing conditions. The results showed that high amounts of RCP were correlated with high total flavonoid content, whereas the addition of high amounts of vitamin C resulted in higher antioxidant activity. In conclusion, an optimized formulation for the honey-based herbal pill was found to contain 35% RCP, 10% BMP, and 10% vitamin C.

• Explosives and Blasting
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• v.38 no.4
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• pp.16-25
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• 2020

Multi-setting smart-investigation of the ground and large uncharged hole boring (MSP) method to reduce the blast-induced vibration in a tunnel excavation is carried out over 50m of long-distance boring in a horizontal direction and thus has been accompanied by deviations in boring alignment because of the heavy and one-directional rotation of the rod. Therefore, the deviation has been adjusted through the boring machine's variable setting rely on the previous construction records and expert's experience. However, the geological characteristics, machine conditions, and inexperienced workers have caused significant deviation from the target alignment. The excessive deviation from the boring target may cause a delay in the construction schedule and economic losses. A deep learning-based prediction model has been developed to discover an ideal initial setting of the MSP machine. Dropout, early stopping, pre-training techniques have been employed to prevent overfitting in the training phase and, significantly improved the prediction results. These results showed the high possibility of developing the model to suggest the boring machine's optimum initial setting. We expect that optimized setting guidelines can be further developed through the continuous addition of the data and the additional consideration of the other factors.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.6
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• pp.19-26
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• 2021

The lattice structure is attracting attention from industry because of its excellent strength and stiffness, ultra-lightweight, and energy absorption capability. Despite these advantages, widespread commercialization is limited by the difficult manufacturing processes for complex shapes. Additive manufacturing is attracting attention as an optimal technology for manufacturing lattice structures as a technology capable of fabricating complex geometric shapes. In this study, a unit cell was formed using a three-dimensional coordinate method. The relative density relational equation according to the boundary box size and strut radius of the unit cell was derived. Simple cubic (SC), body-centered cubic (BCC), and face-centered cubic (FCC) with a controlled relative density were designed using modeling software. The accuracy of the equations for calculating the relative density proposed in this study secured 98.3%, 98.6%, and 96.2% reliability in SC, BCC, and FCC, respectively. A simulation of the lattice structure revealed an increase in compressive yield load with increasing relative density under the same cell arrangement condition. The compressive yield load decreased in the order of SC, BCC, and FCC under the same arrangement conditions. Finally, structural optimization for the compressive load of a 20 mm × 20 mm × 20 mm structure was possible by configuring the SC unit cells in a 3 × 3 × 3 array.

• Journal of the Korean Crystal Growth and Crystal Technology
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• v.31 no.1
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• pp.55-62
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• 2021

In order to improve fuel economy and reduce CO2, HEV adopts ISG system as a standard. This ISG system increased the electric load that the battery had to bear, and the number of starting increased rapidly. AGM Lead Acid batteries have been developed and used, but the charging time is about three times longer as the electrolyte amount control during formation must be maintained at a higher level compared to conventional lead-acid batteries. In this study, we tried to shorten the charging time by increasing the charging efficiency through the optimization of the formation pattern. In order to optimize the Formation Pattern, 10 charging steps and 6 discharging steps were applied to 16 multi steps, and the charging current for each step was controlled, and the test was conducted under 4 conditions (21 hr, 24 hr, 27 hr, 30 hr). As a result of simultaneous application of multi-step and discharge step, it was verified that minimizing the current loss and eliminating the sudden polarization during charging contributes to the improvement of charging efficiency. As a result, it showed excellent results in reducing the charging time by about 30 % with improved charging efficiency compared to the previous one.

• Journal of the Society of Cosmetic Scientists of Korea
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• v.46 no.4
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• pp.371-382
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• 2020

There have been continuous attempts to quantify sensory attributes of cosmetic products by measuring relevant physical properties. The most representative method to evaluate stickiness is to measure axial force using texture analyzer. Stickiness is known to correlate with AUC which abbreviates area under curve in the obtained axial force curve as a function of time. Recently, Normandie University research group developed in vivo stickiness evaluation method considering the characteristics of skin along with established evaluation method[8]. Based on the study, we tried to optimize in vivo stickiness evaluation method especially for cosmetic creams. The experiment was carried out on 5 different facial creams products by changing the amount and the times of rolling of creams, and the shape and material of probes. Based on the results of the sensory evaluation, the most consistent conditions were established as the optimal evaluation method. As a result, applying 70 μL of cream and rubbing 10 times for 7 s inside the 3.4 cm circle were judged to be suitable. As for the probes, spherical metallic probe was more proper due to its reproducibility. We conducted the settled method on 10 subjects to check its validity. Although the absolute values of AUC differed depending on the individuals, the AUC values were all ranked the same. Finally, for the standardization of stickiness of AUC, polyvinylpyrrolidone (PVP) was set as a reference material and we measured AUC of its aqueous solution by changing concentration. Then, the degree of stickiness recognition for 5 different creams was surveyed to check the correlation between AUC and stickiness.