• Journal of Cadastre & Land InformatiX
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• v.51 no.2
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• pp.83-106
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• 2021

Interests in clean fuels have been soaring because of environmental problems such as air pollution and global warming. Unlike fossil fuels, hydrogen obtains public attention as a eco-friendly energy source because it releases only water when burned. Various policy efforts have been made to establish a hydrogen based transportation network. The station that supplies hydrogen to hydrogen-powered trucks is essential for building the hydrogen based logistics system. Thus, determining the optimal location of refueling stations is an important topic in the network. Although previous studies have mostly applied optimization based methodologies, this paper adopts machine learning to review spatial attributes of candidate locations in selecting the optimal position of the refueling stations. Machine learning shows outstanding performance in various fields. However, it has not yet applied to an optimal location selection problem of hydrogen refueling stations. Therefore, several machine learning models are applied and compared in performance by setting variables relevant to the location of highway rest areas and random points on a highway. The results show that Random Forest model is superior in terms of F1-score. We believe that this work can be a starting point to utilize machine learning based methods as the preliminary review for the optimal sites of the stations before the optimization applies.

• Applied Chemistry for Engineering
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• v.35 no.3
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• pp.239-247
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• 2024

When a fire occurs on a naval vessel, rapid suppression and control are essential to mitigate potential human and material losses. Due to the nature of naval vessels, the risk of fuel fires is significant, making the use of aqueous film-forming foam (AFFF) crucial for effective fire suppression. Additionally, the possibility of fires occurring within compartments on the vessel must also be considered. Understanding the trajectory and application range of AFFF in such environments is vital, necessitating the design of firefighting systems tailored to compartmental conditions. In this study, an analysis was conducted to investigate the feasibility of applying spray height and angle for AFFF using computational fluid dynamics (CFD) methodology as a validation tool. Based on these findings, CFD analysis results applicable to compartment environments on naval vessels were obtained. These results will serve as the foundation for the development of firefighting systems capable of promptly responding to fuel fires within naval vessel compartments.

• Smart Structures and Systems
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• v.34 no.2
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• pp.97-116
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• 2024

The standard l₁-norm regularization is recently introduced for impact force identification, but generally underestimates the peak force. Compared to l₁-norm regularization, l_p-norm (0 ≤ p < 1) regularization, with a nonconvex penalty function, has some promising properties such as enforcing sparsity. In the framework of sparse regularization, if the desired solution is sparse in the time domain or other domains, the under-determined problem with fewer measurements than candidate excitations may obtain the unique solution, i.e., the sparsest solution. Considering the joint sparse structure of impact force in temporal and spatial domains, we propose a general l_p-norm (0 ≤ p < 1) regularization methodology for simultaneous identification of the impact location and force time-history from highly incomplete measurements. Firstly, a nonconvex optimization model based on l_p-norm penalty is developed for regularizing the highly under-determined problem of impact force identification. Secondly, an iteratively reweighed l₁-norm algorithm is introduced to solve such an under-determined and unconditioned regularization model through transforming it into a series of l₁-norm regularization problems. Finally, numerical simulation and experimental validation including single-source and two-source cases of impact force identification are conducted on plate structures to evaluate the performance of l_p-norm (0 ≤ p < 1) regularization. Both numerical and experimental results demonstrate that the proposed l_p-norm regularization method, merely using a single accelerometer, can locate the actual impacts from nine fixed candidate sources and simultaneously reconstruct the impact force time-history; compared to the state-of-the-art l₁-norm regularization, l_p-norm (0 ≤ p < 1) regularization procures sufficiently sparse and more accurate estimates; although the peak relative error of the identified impact force using l_p-norm regularization has a decreasing tendency as p is approaching 0, the results of l_p-norm regularization with 0 ≤ p ≤ 1/2 have no significant differences.

• Journal of Hydrogen and New Energy
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• v.22 no.3
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• pp.326-332
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• 2011

The authors examined the effects of operating parameters on the $H_2$ production by dark fermentation of the wastewater generated from food waste recycling facilities, in short "food waste wastewater (FWW)". Central composite design based response surface methodology was applied to analyze the effect of initial pH (5.5-8.5) and substrate concentration (2-20 g Carbo. COD/L) on $H_2$ production. The experiment was conducted under mesophilic ($35^{\circ}C$) condition and a heat-treated ($90^{\circ}C$ for 20min)anaerobic digester sludge was used as a seeding source. Although there was a little difference in carbohydrate removal, $H_2$ yield was largely affected by the experimental conditions, from 0.38 to 1.77 mol $H_2$/mol $hexose_{added}$. By applying regression analysis, $H_2$ yield was well fitted based on the coded value to a second order polynomial equation (p = 0.0243): Y = $1.78-0.17X_1+0.30X_2+0.37X_1X_2-0.29X_1{^2}-0.35X_2{^2}$, where $X_1$, $X_2$, and Y are pH, substrate concentration (g Carbo. COD/L), and hydrogen yield (mol $H_2$/mol $hexose_{added}$), respectively. The 2-D response surface clearly showed a high inter-dependency between initial pH and substrate concentration, and the role of these two factors was to control the pH during fermentation. According to the statistical optimization, the optimum condition of initial pH and substrate concentration were 7.0 and 13.4 g Carbo. COD/L, respectively, under which predicted $H_2$ yield was 1.84 mol $H_2$/mol $hexose_{added}$. Microbial analysis using 16S rRNA PCR-DGGE showed that $Clostridium$ sp. such as $Clostridium$ $perfringens$, $Clostridium$ $sticklandii$, and $Clostridium$ $bifermentans$ were main $H_2$-producers.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.46 no.8
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• pp.22-30
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• 2009

Due to high levels of integration and complexity, the Network-on-Chip (NoC) approach has emerged as a new design paradigm to overcome on-chip communication issues and data bandwidth limits in conventional SoC(System-on-Chip) design. In particular, exponentially growing of energy consumption caused by high frequency, synchronization and distributing a single global clock signal throughout the chip have become major design bottlenecks. To deal with these issues, a globally asynchronous, locally synchronous (GALS) design combined with low power techniques is considered. Such a design style fits nicely with the concept of voltage-frequency-islands (VFI) which has been recently introduced for achieving fine-grain system-level power management. In this paper, we propose an efficient design methodology that minimizes energy consumption by VFI partitioning on an NoC architecture as well as assigning supply and threshold voltage levels to each VFI. The proposed algorithm which find VFI and appropriate core (or processing element) supply voltage consists of traffic-aware core graph partitioning, communication contention delay-aware tile mapping, power variation-aware core dynamic voltage scaling (DVS), power efficient VFI merging and voltage update on the VFIs Simulation results show that average 10.3% improvement in energy consumption compared to other existing works.

• Korean Journal of Food Science and Technology
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• v.41 no.6
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• pp.622-627
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• 2009

The objectives of this study were to evaluate a protease suitable for the enzymatic hydrolysis of a snow crab processing by-product (SPB) and to optimize the hydrolysis conditions using response surface methodology (RSM). The SPB was hydrolyzed at $50^{\circ}C$ and pH 7.0-7.2 to obtain various degree of hydrolysis (DH) using Flavourzyme at an enzyme/substrate (E/S) ratio of 3.0%. The reaction progress curve exhibited an initial fast reaction rate followed by a slowing of the rate. The DH was increased to 30% at 90 min with a final DH 32 to 36%. A central composite experimental design having three independent variables (reaction temperature, reaction time, and E/S ratio) with five levels was used to optimize the enzymatic hydrolysis conditions. Based on the DH data, the optimum reaction conditions for the enzymatic hydrolysis of the SPB were a temperature of $51.8^{\circ}C$, reaction time of 4 hr 45 min, and an E/S ratio of 3.8%. It was demonstrated that the enzymatic hydrolysate of SPB could be used as a flavoring agent or a source of precursors for the production of reaction flavors.

• Korean journal of food and cookery science
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• v.22 no.1 s.91
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• pp.22-29
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• 2006

Yogurt base was prepared from milk powder $(14\sim18%)$ to which was added 0.4% Saururus chinensis (Lour.) Bail water extract (SCE) and fermented with lactic acid bacteria (a mixed strain of Streptococcus thermophilus and Lactobacillus bulgaricus) at $37^{\circ}C$ for 24 hr. The viscosity of the yogurt added SCE (SCE yogurt) made from 18% milk was higher than that of SCE yogurt containing $14\sim16%$ milk, whereas the pH and titratable acidity of the SCE yogurt were not significantly different on the range of milk contents. The optimal milk concentration for SCE yogurt manufacture was 18%. In order to optimize the preparation of dressing from SCE yogurt, the central composite design was conducted in terms of the yogurt (30, 40, 50, 60, 70 g), the mayonnaise (6, 12, 18, 24, 30 g) and the salt (0.1, 0.3, 0.5, 0.7, 0.9 g) contents. Sensory evaluation was performed and evaluated using a response surface methodology. The optimum ingredient ratio for SCE yogurt dressing was determined to be 61.2% of yogurt, 23.5% of mayonnaise, 0.58% of salt, 0.58% of honey, 1.75% of mustard, 0.23% of Tabasco pepper sauce, 0.94% of wine and 0.04% of white pepper.

• Korean Journal of Food Science and Technology
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• v.36 no.4
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• pp.531-536
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• 2004

Synthesis conditions were optimized using response surface methodology for producing structured lipids (SL) by interesterification of DHA-enriched algae oil derived from microalgae, Schizochytrium sp. and corn oil. Reaction was performed fer 24 hr at $55^{\circ}C$ catalyzed by immobilized lipase from Rhizomucor miehei (RM IM) in shaking water bath. Major fatty acids of SL were palmitic (21.70 mol%), oleic (20.20 mol%), and linoleic (27.34 mol%) acids, and DHA (15.06 mol%). To separate newly synthesized SL-triglycerides (TG) species, HPLC with evaporative light scatting detector (ELSD) was used. Production conditions were optimized using central composite design with reaction temperature $(35-75^{\circ}C,\;X_1)$, reaction time $(2-42\;hr,\;X_2)$, and enzyme concentration $(2-14%,\;X_3)$ as variables. When variables were $70.28^{\circ}C\;(X_1),\;28.74\;hr\;(X_2),\;and\;11.30%\;(X_3)$, maximum content of selected three peaks of synthesized SL-TG species was predicted as 6.97 area%.

• Food Science and Preservation
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• v.15 no.6
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• pp.832-839
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• 2008

The stock that is the first step for preparation of soups and purees links to the taste of food. Many types of vegetable have been used in stocks, but this study focused on stocks prepared with sweet pumpkin. The stock preparation conditions including the weight of sweet pumpkin, the water volume, and the boiling time at $97^{\circ}C$ were optimized by response surface methodology. The quality characteristics of the resulting stock were investigated. The color, flavor, taste and overall acceptability were dependent parameters. A model equation was proposed with regard to the sweet pumpkin weight, water volume, and boiling time at $97^{\circ}C$. A sweet pumpkin weight of 357.9 to 403.0 g, a water volume of 689.8 to 768.5 mL, and a boiling time of 9.9 to 10.3 min at $97^{\circ}C$ were found to be the optimal stock preparation conditions. The quality characteristics of the sweet pumpkin stock prepared under the optimized conditions were pH 6.64, total acidity 0.18%, soluble solids $2.39\;^{\circ}Brix$, color value (L, 99.07 a, -2.43 b, 11.82), total polyphenol 280.75 mg/L, and electron donating ability 21.32%.

• Journal of the Korean Society of Food Science and Nutrition
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• v.33 no.10
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• pp.1735-1741
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• 2004

Preparation conditions for germinated brown rice gruel on its sensory quality were optimized using response surface methodology. Water volume ratio to germinated brown rice significantly affected the sensory quality of germinated brown rice gruel. Sensory quality, such as color, flavour, and overall acceptance increased significantly when milk ratio was increased. R2 of response surface equations were 0.9076, 0.9634, 0.9555, 0.9677 and 0.9769 for color, viscosity, flavour, mouthfeel and overall acceptance respectively (p<0.01). Optimum preparation conditions on overall acceptance for germinated brown rice gruel were: water volume ratio 8.26, cooking time 31.98 min, cooking temperature 95.71$^{\circ}C$ and milk ratio 0.54. High correlation was found between viscosity, flavour, mouthfeel, and overall quality.