• Design & Manufacturing
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• v.17 no.4
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• pp.1-7
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• 2023

In the fabrication of curved multi-display glass for automotive use, the surface roughness of the mold is a critical quality factor. However, the difficulty in detecting micro-cutting signals in a micro-machining environment and the absence of a standardized model for predicting micro-cutting forces make it challenging to intuitively infer the correlation between cutting variables and actual surface roughness under machining conditions. Consequently, current practices heavily rely on machining condition optimization through the utilization of cutting models and experimental research for force prediction. To overcome these limitations, this study employs a surface roughness prediction formula instead of a cutting force prediction model and converts the surface roughness prediction formula into experimental data. Additionally, to account for changes in surface roughness during machining runtime, the theory of position variables has been introduced. By leveraging artificial neural network technology, the accuracy of the surface roughness prediction formula model has improved by 98%. Through the application of artificial neural network technology, the surface roughness prediction formula model, with enhanced accuracy, is anticipated to reliably perform the derivation of optimal machining conditions and the prediction of surface roughness in various machining environments at the analytical stage.

• Steel and Composite Structures
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• v.51 no.1
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• pp.25-41
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• 2024

The measurement of pile bearing capacity is crucial for the design of pile foundations, where in-situ tests could be costly and time needed. The primary objective of this research was to investigate the potential use of fuzzy-based techniques to anticipate the maximum weight that concrete driven piles might bear. Despite the existence of several suggested designs, there is a scarcity of specialized studies on the exploration of adaptive neuro-fuzzy inference systems (ANFIS) for the estimation of pile bearing capacity. This paper presents the introduction and validation of a novel technique that integrates the fire hawk optimizer (FHO) and equilibrium optimizer (EO) with the ANFIS, referred to as ANFIS_FHO and ANFIS_EO, respectively. A comprehensive compilation of 472 static load test results for driven piles was located within the database. The recommended framework was built, validated, and tested using the training set (70%), validation set (15%), and testing set (15%) of the dataset, accordingly. Moreover, the sensitivity analysis is performed in order to determine the impact of each input on the output. The results show that ANFIS_FHO and ANFIS_EO both have amazing potential for precisely calculating pile bearing capacity. The R² values obtained for ANFIS_FHO were 0.9817, 0.9753, and 0.9823 for the training, validating, and testing phases. The findings of the examination of uncertainty showed that the ANFIS_FHO system had less uncertainty than the ANFIS_EO model. The research found that the ANFIS_FHO model provides a more satisfactory estimation of the bearing capacity of concrete driven piles when considering various performance evaluations and comparing it with existing literature.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.17 no.5
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• pp.313-322
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• 2024

To ensure the stable flight of aerospace electric propulsion systems, it is necessary to measure the supplied flow rate and control it to an appropriate level. However, conventional flow sensors are costly and face limitations in space environments, making heat-based flow estimation a promising alternative. In this study, the Taguchi method, one of the experimental design techniques, was applied to perform thermal analysis simulations using Ansys under various variables and conditions. The Taguchi method was used to set heat supply and the positioning of inlet and outlet temperature sensors as key variables, and the optimal distance conditions were derived. Thermal analysis was conducted through Ansys to analyze the flow estimation results under each experimental condition. Therefore, this study demonstrates the practicality of the heat-based flow estimation method for fuel management systems in electric propulsion systems, presenting a new approach for the efficient and economical operation of electric propulsion. Additionally, this research contributes to the development of fuel management technologies that can be effectively utilized in the constrained environment of space.

• Clean Technology
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• v.30 no.3
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• pp.188-194
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• 2024

This study investigates the impact of reduction temperature on the structure and performance of cobalt-manganese (CM) based catalysts in the direct hydrogenation reaction of carbon dioxide (CO₂). It was observed that at a reduction temperature of 350 ℃, these catalysts could successfully facilitate the conversion of CO₂ into long-chain hydrocarbons. This efficiency is attributed to the optimal conditions provided by the core-shell structure of the catalysts, which effectively catalyzes both the reverse water-gas shift (RWGS) and Fischer-Tropsch (FT) reactions. However, as the reduction temperature increased to 600 ℃, the effectiveness of the reaction process was hindered, and there was a shift in selectivity towards methane. This shift is due to the excessive reduction of the catalyst's outer shell, which reduces the number of RWGS sites and subsequently suppresses the production of CO. These findings highlight the importance of carefully controlling the reduction temperature in the design and optimization of cobalt-based catalysts. Maintaining a balance between the RWGS and FT reactions is crucial. This emphasizes that the reduction temperature is a key factor in efficiently generating long-chain hydrocarbons from CO₂.

• Food Science and Preservation
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• v.15 no.1
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• pp.49-57
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• 2008

This study was conducted to develop an optimal composite recipe for a cookie including yam powder that would be attractive to all age groups. Wheat flour was partially substituted by yam powder to reduce the content of wheat flour. This study has produced the sensory optimal composite recipe by making cookies, respectively with each 5 level of yam powder $(X_1)$, Sugar$(X_2)$, butter$(X_3)$, by C.C.D (Central Composite Design) and conducting sensory evaluation and instrumental analysis by means of RSM (Response Surface Methodology). Sensory items showed very significant values in color, softness, overall quality (p<0.01), flavor (p<0.05) and those of instrumental analysis showed significant values in lightness, redness (p<0.05), spread ratio, hardness (p<0.01). Also sensory optimal ratio of yam cookie was calculated at yam powder 37.35 g, sugar 50.75 g, butter 78.40 g and it was revealed that the factors of influencing yam cookie aptitude were in older of yam powder, butter, sugar.

• Food Science and Preservation
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• v.20 no.6
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• pp.810-817
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• 2013

This study investigated the properties of rice snack puffed in a microwave oven after drying its dough according to Baekjinju soaking time and additional soybean milk. The optimum conditions for the non-fried rice snack using Baekjinju wetted flour were determined through the design of an experiment using response surface methodology. The independent variables were the Baekjinju soaking time and the additional soybean milk, and the dependent variables were the weight, volume, density, expansibility, Hunter's color value, hardness, and sensory properties. The quadratic model was chosen for the weight, density, expansibility, b value, and hardness. The two-factor interaction model was chosen for the volume, flavor, appearance, and overall preference. The linear model was chosen for the L value, taste, and texture. The weight was increased to longer than 11.26 days with the increase in the rice soaking. The volume, expansibility, L value, and b value increased with the increase in the rice soaking time and in the additional soybean milk ratio. However, the density was decreased was in reverse. The hardness increased most, with the rice soaking time rising from 5.28 to 8.53 days and the soybean milk additional ratio increasing from 5.34 to 20.26%. The sensory properties improved as rice soaking time decreased, and the soybean milk additional ratio was revered. As for the desirability, the optimal formulation of the dough of non-fried rice snack was achieved by mixing 200 g of Baekjinju flour with a 0.69 days rice soaking time and a 26.67% soybean milk of rice ratio according to weight.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.35 no.1
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• pp.53-60
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• 2011

In this study, an organic Rankine-cycle system using HFC-134a, which is a power cycle corresponding to a low-temperature heat source, such as that for geothermal power generation, was investigated from the view point of power optimization. In contrast to conventional approaches, the heat transfer and pressure drop characteristics of the working fluid within the heat exchangers were taken into account by using a discretized heat exchanger model. The inlet flow rates and temperatures of both the heat source and the heat sink were fixed. The total heat transfer area was fixed, whereas the heat-exchanger areas of the evaporator and the condenser were allocated to maximize the power output. The power was optimized on the basis of three design parameters. The optimal combination of parameters that can maximize power output was determined on the basis of the results of the study. The results also indicate that the evaporation process has to be optimized to increase the power output.

• Microbiology and Biotechnology Letters
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• v.41 no.4
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• pp.398-406
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• 2013

For the maximal production of aphicidal metabolites produced by the Beauveria bassiana Bb08, statistical methods such as the Box-Behnken experimental design and response surface methodology were used. The fungal culture filtrate was sprayed towards 3-star aphids and the mortality was examined. After the statistical analysis of the aphid mortality, the optimal culture conditions were found to be a culture temperature of $26.2^{\circ}C$, medium pH 5.9, flask shaking speed of 209.0 rpm, and culture time of 5.9 days. The expected mortality on days 4, 5, and 6 after spraying the filtrate on to the aphids were 76.8%, 84.9%, and 89.4%, respectively. All 4 factors of the culture conditions significantly affected the production of the aphicidal metabolites, and the order of significance was temperature, pH, culture time and shaking speed.

• Food Science and Preservation
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• v.18 no.2
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• pp.178-183
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• 2011

The consumer awareness concerning coffee beverages has increased in Korea. The objective of this study was to optimize the roasting conditions of coffee bean for consumer's attribute. The optimal roasting conditions for Colombian coffee beans were analyzed by using a central composite design with a quadratic polynomial model by response surface methodology (RSM). The experimental conditions for coffee bean roasting were $194.82^{\circ}C{\sim}250.00^{\circ}C$ and 7.93~22.07 minutes. The responses of sensory attributes. physicochemical and physical properties were analyzed with RSM. The width. length and height of green beans increased when the beans were roasted. The higher degree of roasting gave the higher pH and solid contents but the lower total acidity and total phenolic compounds. In sensory tests, the roasting temperature and time had a significant effect on the flavor score. The optimum roasting condition of Colombian coffee bean predicted for maximizing the length, width, solid contents, total phenolic compounds and flavor score were 20 minutes at $225^{\circ}C$ by RSM.

• Journal of the Korean Society of Food Science and Nutrition
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• v.43 no.9
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• pp.1462-1466
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• 2014

In this study, an attempt was made to produce oat protein concentrates from defatted oat groat by alkali extraction. Independent variables formulated by D-optimal design were NaOH concentration (X1, 0.005~0.06 N) for extraction and precipitation pH (X2, pH 4.0~6.0), and the dependent variable was extraction yield (Y1, %). Experimental results were analyzed by response surface methodology to determine optimized extraction conditions. Extraction yield increased both with an increase in NaOH concentration of the extraction solution and when approaching a precipitation pH of 4.9, and NaOH concentrations were a major influencing parameter. Solubility of oat protein concentrates showed a minimum value (i.e., 0.1%) at pH 5 and increased substantially at pH values in the range of ${\leq}$ pH 3 or ${\geq}$ pH 7, reaching a maximum value at pH 11 (i.e., 76%). Regression equation coincided well with the results of the experiment. Optimized extraction conditions to maximize extraction yield were 0.06 N NaOH (X1) for extraction and pH 4.7 (X2) for precipitation.