• Food Science and Preservation
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• v.15 no.3
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• pp.332-339
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• 2008

This study was performed to investigate the sorption characteristics and shelf-life of coated ascorbic acid Stability of ascorbic acid, which oxidizes easily during storage and processing, was achieved by applying a fluidized bed coating using Zein-DP and HPMC-FCC as covering materials. The monolayer moisture content calculated using the GAB equation showed a higher level of significance than when calculated using the BET equation. The fit to the isotherm curve was in the order of Halsey, Caurie, Oswin and Khun. The equilibrium relative humidity prediction model was established in terms of time and water activity, it had higher significance. The stability of the coated ascoribic acid during storage was investigated in terms of radical-scavenging activity, which decreased with increasing time of storage and was more affected at higher storage temperatures. The quality reduction rate constant (k) was calculated by a first-order reaction rate. The reaction rate constant increased with increasing storage temperature. The shelf-life of Zein-DP-coated ascorbic acid was estimated to be 45.83 days at 20C and 63.19 days at 10C, and the shelf-life for HPMC-FCC-coated ascorbic acid was estimated to be 28.84 days at 20C and 36.14 days at 10, the ascorbic acid was 24.52 days at $20^{\circ}C$ and 27.22 days at $10^{\circ}C$, respectively. Therefore, the fluidized bed coating effectively increased the stability of ascorbic acid.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.27 no.4
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• pp.289-296
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• 2014

The rebar detailing is an important work influencing the final performance and quality of RC structures. But it is one of the most irrational and illogical activity in construction site. Many groups of workers, including main contractors, structural engineers, shop drawers, rebar fabricators, and etc., participate in this activity. A loosely-organized process for this activity is apt to produce a big amount of rebar loss or even degraded structures. A 3-dimensional rebar auto-placing system, called as Rebar Hub, has been designed and implemented in this research. Rebar Hub provides a totally integrated service from 3D structural modeling of buildings to rebar auto-placing considering anchorage, splice, and the length of ordered rebar. In addition, Rebar Hub can recognize the 2D drawing CAD files and then build 3D structural models which are used for the start point of 3D rebar auto-placing. After rebar auto-placing, each members of the 3D structural model have rebar information belonging to them. It means that the rebar information can be used for the afterward works such as quantity-survey, manufacturing and fabrication of rebars. Rebar Hub is showing outstanding performance while applying to practical projects. It has almost five times productivity and reduces the rebar loss up to 3~8% of the initially-surveyed amount of rebar.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.13 no.5
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• pp.323-330
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• 2020

This paper proposes the road roughness based Braking Pressure Calculation System(BPCS) for an Autonomous Vehicle Stability. The system consists of an image normalization module that processes the front image of a vehicle to fit the input of the random forest, a Random Forest based Road Roughness Classification Module that distinguish the roughness of the road on which the vehicle is travelling by using the weather information and the front image of a vehicle as an input, and a brake pressure control module that modifies a friction coefficient applied to the vehicle according to the road roughness and determines the braking strength to maintain optimal driving according to a vehicle ahead. To verify the efficiency of the BPCS experiment was conducted with a random forest model. The result of the experiment shows that the accuracy of the random forest model was about 2% higher than that of the SVM, and that 7 features should be bagged to make an accurate random forest model. Therefore, the BPCS satisfies both real-time and accuracy in situations where the vehicle needs to brake.

• Smart Media Journal
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• v.11 no.5
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• pp.9-16
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• 2022

Recently, agricultural sites are automating into digital agricultural smart farms by applying technologies such as big data and Internet of Things (IoT). These smart farms aim to increase production and improve crop quality by measuring the environment of crops, investigating and processing data. Production prediction is an important study in smart farm digital agriculture, which is a high-tech agriculture, and it is necessary to analyze environmental data using big data and further standardized research to manage the quality of growth information data. In this paper, environmental and production data collected from smart farm strawberry farms were analyzed and studied. Based on regression analysis, crop production prediction models were analyzed using Ridge Regression, LightGBM, and XGBoost. Among the three models, the optimal model was XGBoost, and R2 showed 82.5 percent explanatory power. As a result of the study, the correlation between the amount of positive fluid absorption and environmental data was confirmed, and significant results were obtained for the production prediction study. In the future, it is expected to contribute to the prevention of environmental pollution and reduction of sheep through the management of sheep by studying the amount of sheep absorption, such as information on the growing environment of crops and the ingredients of sheep.

• Korean Journal of Food Science and Technology
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• v.51 no.2
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• pp.160-168
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• 2019

This study aimed to determine whether double-processed ginseng berry extract (PGBC) could improve learning and memory in an $A\hat{a}42$-induced Alzheimer's mouse model. Passive avoidance test (PAT) and Morris water-maze test (MWMT) were performed after mice were treated with PGBC, followed by acetylcholine (ACh) measurement and glial fibrillary acidic protein (GFAP) detection for brain damage. Furthermore, acetylcholinesterase (AChE) activity and choline acetyltransferase (ChAT) expression were analyzed using Ellman's and qPCR assays, respectively. Results demonstrated that PGBC contained a high amount of ginsenosides (Re, Rd, and Rg3), which are responsible for the clearance of $A{\hat{a}} 42$. They also helped to significantly improve PAT and MWMT performance in the $A{\hat{a}} 42-induced$ Alzheimer's mouse model when compared to the normal group. Interestingly, ACh and ChAT were remarkably upregulated and AChE activities were significantly inhibited, suggesting PGBC to be a palliative adjuvant for treating Alzheimer's disease. Altogether, PGBC was found to play a positive role in improving cognitive abilities. Thus, it could be a new alternative solution for alleviating Alzheimer's disease symptoms.

• Journal of Intelligence and Information Systems
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• v.29 no.1
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• pp.121-142
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• 2023

As the number and weight of imported food are steadily increasing, safety management of imported food to prevent food safety accidents is becoming more important. The Ministry of Food and Drug Safety conducts on-site inspections of foreign food facilities before customs clearance as well as import inspection at the customs clearance stage. However, a data-based safety management plan for imported food is needed due to time, cost, and limited resources. In this study, we tried to increase the efficiency of the on-site inspection by preparing a machine learning prediction model that pre-selects the companies that are expected to fail before the on-site inspection. Basic information of 303,272 foreign food facilities and processing businesses collected in the Integrated Food Safety Information Network and 1,689 cases of on-site inspection information data collected from 2019 to April 2022 were collected. After preprocessing the data of foreign food facilities, only the data subject to on-site inspection were extracted using the foreign food facility_code. As a result, it consisted of a total of 1,689 data and 103 variables. For 103 variables, variables that were '0' were removed based on the Theil-U index, and after reducing by applying Multiple Correspondence Analysis, 49 characteristic variables were finally derived. We build eight different models and perform hyperparameter tuning through 5-fold cross validation. Then, the performance of the generated models are evaluated. The research purpose of selecting companies subject to on-site inspection is to maximize the recall, which is the probability of judging nonconforming companies as nonconforming. As a result of applying various algorithms of machine learning, the Random Forest model with the highest Recall_macro, AUROC, Average PR, F1-score, and Balanced Accuracy was evaluated as the best model. Finally, we apply Kernal SHAP (SHapley Additive exPlanations) to present the selection reason for nonconforming facilities of individual instances, and discuss applicability to the on-site inspection facility selection system. Based on the results of this study, it is expected that it will contribute to the efficient operation of limited resources such as manpower and budget by establishing an imported food management system through a data-based scientific risk management model.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.17 no.6
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• pp.31-38
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• 2003

Among mitigation techniques for electric and magnetic field (EMF) from an overhead transmission line a passive loop is a way that can be cheap and easily installed on the existing towers and have a satisfactory effect as well. However current induced in the passive loop causes transmission power loss and the phase imbalance increases since geometrical asymmetry of the transmission lines becomes larger. So in order to evaluate the power loss and the phase imbalance due to a passive loop, this paper represent a 345[kV] 1-circuit flat type transmission line as asymmetrical 3-phase distributed parameter line model where the effect of a passive loop is embedded in the line parameters, and then formulates differential equations. By solving these equations voltages and currents of each phase at receiving end become known. We find out that power losses occur differently at each phase and positive sequence component decreases at receiving end while negative sequence component increase. In general phase imbalance due to a passive loop is slight, but it increases in proportional to the induced current and length of section where the passive loop is installed. Thus the phase imbalance should be included in terms of cost for introducing a passive loop.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.18 no.10
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• pp.42-47
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• 2017

In this study,we conducted an injection molding analysis of metal powder materials for the development of flanges, which are necessary adapters for optical communication. The metal powder injection molding process is a technique for producing an injection molded article having a complicated shape by mixing ceramic or stainless powder and binders. It is used to produce products which require complex processing technology or for which the productivity is low. The purpose of this study is to minimize the manufacturing processing of products which are manufactured through existing mechanical processing procedures. For the injection molding analysis, we mixed stainless STS316 metal powder with binders at a ratio of 6 to 4 to make molding materials consisting of granular pellets. Then, three-dimensional modeling and meshing were carried out to obtain the optimal injection molding analysis conditions(molding temperature, melting temperature, injection time, injection temperature, injection pressure, packing time and cooling time). As a result of the analysis, it was discovered that the inlet became available 13.29 seconds after the first injection. Also, as the flowing and packing in the melt through the sprue, runner and gate were stable, it is expected that good molds can be manufactured.

• Korean Journal of Food Science and Technology
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• v.53 no.6
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• pp.739-748
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• 2021

This study focuses on the use of rice in the production of gluten-free rice udon (GFU) through an optimized mixing ratio, using the Box-Behnken response surface methodology (RSM). Different additional levels of rice flour (A, 40-60 g), acetylated distarch adipate (B, 10-20 g), and trehalose (C, 0-3 g) were used as variables, while water absorption level, volume, cooking loss, solid yield, lightness, texture properties, proximate compositions of GFU and turbidity of cooking water were set as responses in the RSM design model. The optimum mixing ratio for the preparation of gluten-free rice udon was obtained for 60.00 g of rice flour, 18.81 g of acetylated distarch adipate without the addition of trehalose. The response values of the optimized samples were water absorption (60.94%), volume (34.94%), turbidity of the cooking water (0.37), cooking loss (4.77%), solid yield (1.55 g), lightness value (70.04), hardness (2.53 N), springiness (0.18), gumminess (10.45 N), chewiness (1.83 N), and cohesiveness (2.89). This study has shown that rice flour can replace wheat flour to manufacture udon at an optimized mixing ratio successfully derived by statistical estimation method.

• Korean Journal of Food Science and Technology
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• v.53 no.5
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• pp.593-600
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• 2021

In this study, the vacuum distillation process for producing non-alcoholic red wine was optimized via response surface methodology. As a result of optimizing the responses (alcohol content, yield) for independent variables (operating time, boiling point, and temperature difference), 1% alcohol content and 81.15% yield were obtained at an operating time of 24.5 min, boiling point of 65℃, and temperature difference of 8℃. To investigate the physicochemical and sensory properties, non-alcoholic wines with different boiling points (bp 25℃, bp 45℃, and bp 65℃) and a blended wine (4.2% of control wine added) were prepared. As the boiling point increased, the alcohol content decreased, and CI (color intensity) and Hue increased. Blended wine exhibited the highest value and bp 65℃ showed the lowest value in terms of sensory properties. In conclusion, distillation at a low boiling point and blending control wine could be used to prepare non-alcoholic wine with a high preference.