• Transactions of the Korean Society of Mechanical Engineers A
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• v.36 no.4
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• pp.361-371
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• 2012

In order to improve the efficiency of the branch-and-bound method for mixed-discrete nonlinear programming, a nonuniform convergence tolerance scheme is proposed for the continuous subproblem optimizations. The suggested scheme assigns the convergence tolerances for each continuous subproblem optimization according to the maximum constraint violation obtained from the first iteration of each subproblem optimization in order to reduce the total number of function evaluations needed to reach the discrete optimal solution. The proposed tolerance scheme is integrated with five branching order options. The comparative performance test results using the ten combinations of the five branching orders and two convergence tolerance schemes show that the suggested non-uniform convergence tolerance scheme is obviously superior to the uniform one. The results also show that the branching order option using the minimum clearance difference method performed best among the five branching order options. Therefore, we recommend using the "minimum clearance difference method" for branching and the "non-uniform convergence tolerance scheme" for solving discrete optimization problems.

• Korean Chemical Engineering Research
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• v.53 no.2
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• pp.236-242
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• 2015

We present two data-driven modeling methods, partial least square (PLS) and artificial neural network (ANN), to predict the major operating and performance variables of a polymer electrolyte membrane (PEM) fuel cell stack. PLS and ANN models were constructed using the experimental data obtained from the testing of a 30 kW-class PEM fuel cell stack, and then were compared with each other in terms of their prediction and computational performances. To reduce the complexity of the models, we combined a variables importance on PLS projection (VIP) as a variable selection method into the modeling procedure in which the predictor variables are selected from a set of input operation variables. The modeling results showed that the ANN models outperformed the PLS models in predicting the average cell voltage and cathode outlet temperature of the fuel cell stack. However, the PLS models also offered satisfactory prediction performances although they can only capture linear correlations between the predictor and output variables. Depending on the degree of modeling accuracy and speed, both ANN and PLS models can be employed for performance predictions, offline and online optimizations, controls, and fault diagnoses in the field of PEM fuel cell designs and operations.

• Journal of Korea Water Resources Association
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• v.48 no.5
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• pp.409-423
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• 2015

In this study the very short-term rainfall forecasting and storm water forecasting using the weather radar data were implemented in an urban stream basin. As forecasting time increasing, the very short-term rainfall forecasting results show that the correlation coefficient was decreased and the root mean square error was increased and then the forecasting model accuracy was decreased. However, as a result of the correlation coefficient up to 60-minute forecasting time is maintained 0.5 or higher was obtained. As a result of storm water forecasting in an urban area, the reduction in peak flow and outflow volume with increasing forecasting time occurs, the peak time was analyzed that relatively matched. In the application of storm water forecasting by radar rainfall forecast, the errors has occurred that we determined some of the external factors. In the future, we believed to be necessary to perform that the continuous algorithm improvement such as simulation of rapid generation and disappearance phenomenon by precipitation echo, the improvement of extreme rainfall forecasting in urban areas, and the rainfall-runoff model parameter optimizations. The results of this study, not only urban stream basin, but also we obtained the observed data, and expand the real-time flood alarm system over the ungaged basins. In addition, it is possible to take advantage of development of as multi-sensor based very short-term rainfall forecasting technology.

• Membrane Journal
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• v.26 no.2
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• pp.126-134
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• 2016

To produce renewable biomethane from biogas, the properties of physical absorbents such as water, methanol, 1-methyl-2-pyrrolidone (NMP), poly(ethylene glycol) dimethylether (PEGDME), and propylene carbonate (PC) were studied, and PC was applied to membrane contactor systems. Among physical absorbents, PC exhibited a high contact angle of $58.3^{\circ}$ on polypropylene surface, and a PC/water mixture (5 wt%) increased the contact angle to $90^{\circ}$. Furthermore, the PC/water mixture presented higher $CO_2$ absorption capacities (0.148-0.157 mmol/g) than that of water (0.121 mmol/g), demonstrating a good property as an absorbent for membrane contactors. Actual operations in membrane contactors using the PC/water mixture resulted in $CO_2$ removal of 98.0-97.8% with biomethane purities of 98.5-98.3%, presenting a strong potential for biogas treatment. However, the PC/water mixture yielded moderate improved in $CO_2$ removal and methane recovery, as compared with water in the membrane contactor operation. This is originated from insufficient desorption processes to reuse absorbent and low $CO_2$ flux of the PC/water absorbent. Thus, it is requiring optimizations of membrane contactor technology including development of absorbent and improvement of operation process.

• Korean Chemical Engineering Research
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• v.45 no.1
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• pp.73-80
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• 2007

This article aims to optimize the nitrogen removal of a sequencing batch reactor (SBR) through the use of the activated sludge model and iterative dynamic programming (IDP). Using a minimum batch time and a maximum nitrogen removal for minimum energy consumption, a performance index is developed on the basis of minimum area criteria for SBR optimization. Choosing area as the performance index makes the optimization problem simpler and a proper weighting in the performance index makes it possible to solve minimum time and energy problem of SBR simultaneously. The optimized results show that the optimal set-point of dissolved oxygen affects both the total batch time and total energy cost. For two different influent loadings, IDP-based SBR optimizations suggest each supervisory control of batch scheduling and set-point trajectory of dissolved oxygen (DO) concentration, and can save 20% of the total energy cost, while meeting the treatment requirements of COD and nitrogen. Moreover, it shows that the re-optimization of IDP within a batch can solve the modelling error problem due to the influent loading changes, or the process faults.

• Journal of Life Science
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• v.20 no.5
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• pp.662-669
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• 2010

Lipolytic enzyme-producing bacteria were isolated from edible oil mill effluents on tributyrin agar medium. The shake-flask-scale studies yielded a promising isolate and it was identified as Pseudomonas sp. An OME using various microbiological observations such as cultural, microscopic, and biochemical tests was undertaken and confirmed using PIBWIN bacterial identification software. Lipolytic enzyme production was screened with oils such as sunflower, caster, coconut, tributyrin, and olive. Amongst these, olive oil showed an increased lipase production 6.1 U/ml. In view of the highest lipolytic enzyme production with olive oil, further optimizations were carried out using olive oil as a carbon source. Lipolytic enzyme production was optimized by a conventional 'one variable at a time' approach and the significant factors were further analyzed statistically using response surface methodology (RSM). The effect of physical factors such as incubation time, temperature, initial medium pH, and nutritional factors such as concentration of olive oil and yeast extract were examined for lipase production. Lipolytic enzyme secretion was strongly affected by three variables (incubation time, concentration of yeast extract and olive oil). Therefore, the interaction of these three factors was further optimized using response surface methodology. The optimized conditions of lipase production using response surface methodology yielded a maximum of 9.62 U/ml with optimum conditions for incubation, yeast extract and olive oil concentrations were found to be 48 hr, 0.3 g. and 0.9 ml. respectively.

• Journal of the Korean earth science society
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• v.29 no.3
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• pp.263-279
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• 2008

This study is concerned with the optimization of models using MM5 and WRF mesoscale numerical models to simulate strong sea surface winds, such as that of typhoon Shanshan on 17 September 2006, and the Siberian high event on 16 December 2006, which were selected for displaying the two highest mean wind speeds. The model optimizations for the lowest level altitude, physical parameters and horizontal resolution were all examined. The sea surface wind values obtained using a logarithmic function which takes into account low-level stability and surface roughness were more accurate than those obtained by adjusting the lowest-level of the model to 10 m linearly. To find the optimal parameters for simulating strong sea surface winds various physical parameters were combined and applied to the model. Model grid resolutions of 3-km produced better results than those of 9-km in terms of displaying accurately regions of strong wind, low pressure intensities and low pressure mesoscale structures.

• Journal of Broadcast Engineering
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• v.12 no.6
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• pp.596-610
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• 2007

In order to reduce the complexity of SVC encoding, we introduce a fast mode decision method in the enhancement layers of spatial scalability by selectively performing the inter-layer residual prediction of SVC. The Inter-layer residual prediction coding in Scalable Video Coding has a large advantage of enhancing the coding efficiency since it utilizes the correlation between two residuals from a lower spatial layer and its next higher spatial layer. However, this entails the dramatical increase in the complexity of SVC encoders. The proposed method is to analyze the characteristics of integer transform coefficients for the subtracted signal for two residuals from lower and upper spatial layers. Then it selectively performs the inter-layer residual prediction coding and rate-distortion optimizations in the upper spatial enhancement layer if the SAD values of residuals exceed adaptive threshold values. Therefore, by classifying the residuals according to the properties of integer-transform coefficients only with SAD of residuals between two layers, the SVC encoder can perform the inter-layer residual coding selectively, thus significantly reducing the total required encoding time. The proposed method results in reduction of the total encoding time with 51.5% in average while maintaining the RD performance with negligible amounts of quality degradation.

• 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.

• The Journal of the Korea Contents Association
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• v.19 no.5
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• pp.187-193
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• 2019

Key-value storage engines are an essential component of growing demand in many computing environments, including social networks, online e-commerce, and cloud services. Recent key-value storage engines offer many features such as transaction, versioning, and replication. In a key-value storage engine, transaction processing provides atomicity through Write-Ahead-Logging (WAL), and a synchronous commit method for transaction processing flushes log data before the transaction completes. According to our observation, flushing log data to persistent storage is a performance bottleneck for key-value storage engines due to the significant overhead of fsync() calls despite the various optimizations of existing systems. In this article, we propose a group synchronization method to improve the performance of the key-value storage engine. We also design and implement a transaction scheduling method to perform other transactions while the system processes fsync() calls. The proposed method is an efficient way to reduce the number of frequent fsync() calls in the synchronous commit while supporting the same level of transaction provided by the existing system. We implement our scheme on the WiredTiger storage engine and our experimental results show that the proposed system improves the performance of key-value workloads over existing systems.