• Journal of the Korean Society of Food Science and Nutrition
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• v.46 no.3
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• pp.374-380
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• 2017

Image analysis and k-mean clustering were conducted to develop a grading system of dried sea cucumber (SC) based on rehydration rate. The SC images were obtained by taking pictures in a box under controlled light conditions. The region of interest was extracted to depict the shape of the SC in a 2D graph, and those 2D shapes were rendered to build a 3D model. The results from the image analysis provided the morphological features of the SC, including length, width, surface area, and volume, to obtain the parameters of the k-mean clustering weight. The k-mean clustering classified the SC samples into three different grades. Each SC sample was rehydrated at $30^{\circ}C$ for 40 h. During rehydration, the flux of each grade was analyzed. Our study demonstrates that the mass transfer rate of SC increased as the surface area increased, and the grade of SC was classified based on rehydration rate. This study suggests that the optimal rehydration process for SC can be achieved by applying a suitable grading system.

• Transactions of the Korean Society of Automotive Engineers
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• v.20 no.1
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• pp.124-130
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• 2012

An injection mold cooling circuit for an automotive front bumper was optimally designed in order to simultaneously minimize the average of the standard deviations of the temperature and the difference in mean temperatures of the upper and lower molds for uniform cooling. The temperature distribution for a specified design was evaluated by Moldflow Insight 2010, a commercial injection molding analysis tool. For efficient design, PIAnO (Process Integration, Automation and Optimization), a commercial PIDO tool, was used to integrate and automate injection molding analysis procedure. The weighted-sum method was used to handle the multi-objective optimization problem and PQRSM, a function-based sequential approximate optimizer equipped in PIAnO, to handle numerically noisy responses with respect to the variation of design variables. The optimal average of the standard deviations and difference in mean temperatures were found to be reduced by 9.2% and 56.52%, respectively, compared to the initial ones.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.24 no.8
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• pp.627-635
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• 2012

This study aims at developing an artificial neural network(ANN)-based predictive and adaptive temperature control method to control the openings at internal and external skins, and heating systems used in a building with double skin envelope. Based on the predicted indoor temperature, the control logic determined opening conditions of air inlets and outlets, and the operation of the heating systems. The optimization process of the initial ANN model was conducted to determine the optimal structure and learning methods followed by the performance tests by the comparison with the actual data measured from the existing double skin envelope. The analysis proved the prediction accuracy and the adaptability of the ANN model in terms of Root Mean Square and Mean Square Errors. The analysis results implied that the proposed ANN-based temperature control logic had potentials to be applied for the temperature control in the double skin envelope buildings.

• Proceedings of the Korean Society of Soil and Groundwater Environment Conference
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• 2003.04a
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• pp.259-262
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• 2003

In the Republic of Korea, Ministry of Construction & Transportation and Korea Water Resources Corporation manage the national groundwater monitoring network at the 169 stations and will organize the supplementary groundwater monitoring network at the 10,000 stations by 2011 year. The method that organizes the monitoring network was developed using the Analytic Hierarchy Process with pairwise comparison. Several estimation factors for the estimating every district were selected to reflect each district conditions. Their weighting value was decided by pairwise comparison and questions to the experts about groundwater The optimal number of groundwater monitoring well was calculated through the developed method. To verify this method, groundwater was monitored in Jeonju city by way showing the example. The study area In Jeonju city needs 7 stations for the supplementary groundwater monitoring network. The results monitored in 7 stations inferred the groundwater level around the study area by Kriging. The mean of residual between inferred groundwater level value from Kriging and actual groundwater level is rather low. Furthermore, the mean and standard deviation of residual between inferred groundwater level change and actual groundwater change is much lower. The Fact that 7 monitoring stations are sufficient for observing the groundwater condition in the study area makes it possible for suggested monitoring number to be proper.

• Journal of Biomedical Engineering Research
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• v.40 no.4
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• pp.132-136
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• 2019

This study proposes an auto-titrating algorithm for auto-titrating positive airway pressure (APAP). The process of the proposed algorithm is as follows. First, sleep apnea-hypopnea and snoring events were detected using nasal pressure. Second, APAP base pressure and SDB events were used for automatic titration of optimal pressure. And, auto-titrating algorithm is built into M3 (MEK-ICS CO. Ltd., Republic of Korea) for evaluation. The detection results of SDB showed mean sensitivity (Sen.) and positive predictive value (PPV.) of 85.7% and 87.8%, respectively. The mean pressure and apnea-hypopnea index (AHI) of auto-titrating algorithm showed $13.0{\pm}5.2cmH_2O$ and $3.0{\pm}2.4$ events/h, respectively. And, paired t-test was conducted to verify whether the performance of our algorithm has no significant difference with AutoSet S9 (p>0.05). These results represent better or comparable outcomes compared to those of previous APAP devices.

• Journal of Korean Society for Quality Management
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• v.52 no.1
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• pp.43-56
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• 2024

Purpose: The injection molding process, crucial for plastic shaping, encounters difficulties in sustaining product quality when replacing injection machines. Variations in machine types and outputs between different production lines or factories increase the risk of quality deterioration. In response, the study aims to develop a system that optimally adjusts conditions during the replacement of injection machines linked to molds. Methods: Utilizing a dataset of 12 injection process variables and 52 corresponding sensor variables, a predictive model is crafted using Decision Tree, Random Forest, and XGBoost. Model evaluation is conducted using an 80% training data and a 20% test data split. The dependent variable, classified into five characteristics based on temperature and pressure, guides the prediction model. Bayesian optimization, integrated into the selected model, determines optimal values for process variables during the replacement of injection machines. The iterative convergence of sensor prediction values to the optimum range is visually confirmed, aligning them with the target range. Experimental results validate the proposed approach. Results: Post-experiment analysis indicates the superiority of the XGBoost model across all five characteristics, achieving a combined high performance of 0.81 and a Mean Absolute Error (MAE) of 0.77. The study introduces a method for optimizing initial conditions in the injection process during machine replacement, utilizing Bayesian optimization. This streamlined approach reduces both time and costs, thereby enhancing process efficiency. Conclusion: This research contributes practical insights to the optimization literature, offering valuable guidance for industries seeking streamlined and cost-effective methods for machine replacement in injection molding.

• The Korean Journal of Financial Management
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• v.25 no.3
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• pp.33-78
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• 2008

This paper empirically examines whether firms engage in a dynamic adjustment process toward target capital structure and, whether there is a target capital structure or mean reverting using the partial adjustment model while allowing for costly adjustment. Also we investigate the empirical determinants of optimal target capital structure in long term equilibrium. As a result, our empirical model captures at least several important features of capital structure behavior for Korean listed firms. First, Korean firms pursue target capital structure and also there is mean reverting phenomenon. Second, Non-Chaebol and small firm in adjustment speed is faster than Chaebol and large firm. Third, even capital market restricts the adjustment speed interestingly. Fourth, Korean firms have target behavior according to a degree of observed gap. Fifth, Korean firms close about one-fourth of the gap between their actual and target debt ratios within one year and thence targeting behavior explains far more of the observed changes in capital structure than market timing or pecking order considerations. Sixth, capital market is significant in determining optimal capital structure.

• Transactions of the Korean Society of Mechanical Engineers
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• v.7 no.3
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• pp.263-269
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• 1983

Underwater welding by a gravity arc welding process was investigated by using six types of coated electrodes and SM41A steel plates of 10 mm thickness as base metal and it was ascertained that this process may be put to practical use. Main results obtained are summarized as follows: 1. Angle of electrode affects no influence on bead appearance and the proper range of welding current and diameter of electrode for the high titanium oxide type is relatively wider than that for the ilmenite type. And the lime titania type, high titanium oxide type and ilmenite type of domestic coated arc welding electrodes of .phi.4 mm could attain the soundest underwater welded joints which contain no welding imperfection. 2. According to macro-structure, micro-structure and hardness distribution inspectionson underwater welded joint, the area between the HAZ and the surface of the weld in neighbourhood of the bond has the maximum hardness value. The structure of these parts is martensite and bainite. Other parts contain mocro-ferrite, micro-pearlite structure, which contain soundness of welded joint free from weld imperfection. 3. On consideration of both tensile strength of more than 100% joint efficiency and sufficient impact value, the welding condition which can get optimal welding strength is heat input of 1,400-1,500 J/mm, current of 200-215 ampere (voltage of 32-33 volts) in the case of lime titania type electrode. 4. Underwater welding strength (tensile strength, impact strength) depends on heat input (or current) quantitatively and they have the relationship of parabolic function. Each experimental equation has a high reliability and its percent of mean error is 4.14%. 5. It is suggested that the optimal design of weld strength by welding condition (current, heat input) could be utilized for a quality control of underwater welding.

• Journal of the Korean Operations Research and Management Science Society
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• v.12 no.1
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• pp.1-9
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• 1987

This paper considers (S -1, S) inventory models which have wide applications in reparable spare parts inventory systems and multi-echelon systems. We assume a discrete compounds Poisson demand and order size dependent delivery times ; when the replenishment order size is n, we assume the delivery time distribution is arbitrary with finite mean $b_{n}$ . On the basis of the fact the outstanding orders follow a certain queueing process, we introduce the results of Fakinos (1982). We develop the efficient recursive formulae to find the optimal $S^{*}$ under several performance measures as a function of the decision variable S. The results of this paper can be applied to the multi-echelon systems such as MEETRIC.C.

• Microbiology and Biotechnology Letters
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• v.23 no.6
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• pp.763-769
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• 1995

As a mean to recover photosynthetic bacterial(PSB) cells and its practical uses in food industrial wastewater treatment, various biodegradable polyelectrolytes were first investigated for flocculation of suspended colloids in the PSB treatment process of soybean curd wastewater. Anionic polyelectrolytes such as sodium alginate and carrageenan were not effective but a cationic polyelectrolyte chitosan isolated from Portunus trituberclatus showed very effective flocculation activity. The concentration of chitosan, pH and temperature of wastewater for maximal flocculation were 40 mg/l, pH 7 and room temperature, respectively. Test using deacetylated chitosan to various degree showed higher flocculating activities in samples deacetylated over 75% and time for maximum flocculation was 40 min by stirring slowly under the above optimal conditions. Chitosan was not only effective to flocculate cells but also removed COD and MLSS of the wastewater. COD of 42% and MLSS of 87% were removed by addition of chitosan to the soybean curd wastewater treated with PSB.