• Journal of Internet Computing and Services
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• v.21 no.6
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• pp.23-31
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• 2020

This study was carried out to generate various images of railroad surfaces with random defects as training data to be better at the detection of defects. Defects on the surface of railroads are caused by various factors such as friction between track binding devices and adjacent tracks and can cause accidents such as broken rails, so railroad maintenance for defects is necessary. Therefore, various researches on defect detection and inspection using image processing or machine learning on railway surface images have been conducted to automate railroad inspection and to reduce railroad maintenance costs. In general, the performance of the image processing analysis method and machine learning technology is affected by the quantity and quality of data. For this reason, some researches require specific devices or vehicles to acquire images of the track surface at regular intervals to obtain a database of various railway surface images. On the contrary, in this study, in order to reduce and improve the operating cost of image acquisition, we constructed the 'Defective Railroad Surface Regeneration Model' by applying the methods presented in the related studies of the Generative Adversarial Network (GAN). Thus, we aimed to detect defects on railroad surface even without a dedicated database. This constructed model is designed to learn to generate the railroad surface combining the different railroad surface textures and the original surface, considering the ground truth of the railroad defects. The generated images of the railroad surface were used as training data in defect detection network, which is based on Fully Convolutional Network (FCN). To validate its performance, we clustered and divided the railroad data into three subsets, one subset as original railroad texture images and the remaining two subsets as another railroad surface texture images. In the first experiment, we used only original texture images for training sets in the defect detection model. And in the second experiment, we trained the generated images that were generated by combining the original images with a few railroad textures of the other images. Each defect detection model was evaluated in terms of 'intersection of union(IoU)' and F1-score measures with ground truths. As a result, the scores increased by about 10~15% when the generated images were used, compared to the case that only the original images were used. This proves that it is possible to detect defects by using the existing data and a few different texture images, even for the railroad surface images in which dedicated training database is not constructed.

• The Journal of Engineering Geology
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• v.30 no.4
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• pp.457-468
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• 2020

Problems arising during pile design works for plant construction, civil and architecture work are mostly come from uncertainty of geotechnical characteristics. In particular, obtaining the N-value measured through the Standard Penetration Test (SPT) is the most important data. However, it is difficult to obtain N-value by drilling investigation throughout the all target area. There are many constraints such as licensing, time, cost, equipment access and residential complaints etc. it is impossible to obtain geotechnical characteristics through drilling investigation within a short bidding period in overseas. The geotechnical characteristics at non-drilling investigation points are usually determined by the engineer's empirical judgment, which can leads to errors in pile design and quantity calculation causing construction delay and cost increase. It would be possible to overcome this problem if N-value could be predicted at the non-drilling investigation points using limited minimum drilling investigation data. This study was conducted to predicted the N-value using an Artificial Neural Network (ANN) which one of the Artificial intelligence (AI) method. An Artificial Neural Network treats a limited amount of geotechnical characteristics as a biological logic process, providing more reliable results for input variables. The purpose of this study is to predict N-value at the non-drilling investigation points through patterns which is studied by multi-layer perceptron and error back-propagation algorithms using the minimum geotechnical data. It has been reviewed the reliability of the values that predicted by AI method compared to the measured values, and we were able to confirm the high reliability as a result. To solving geotechnical uncertainty, we will perform sensitivity analysis of input variables to increase learning effect in next steps and it may need some technical update of program. We hope that our study will be helpful to design works in the future.

• Journal of Mushroom
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• v.18 no.4
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• pp.357-364
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• 2020

The grade and price of Lentinula edodes largely differs in preference depending on the product area and seasonal factors. The product amount of autumn L. edodes was higher than that of spring L. edodes, but high quality, which is divided into "Hwago" is low in preference. Mostly, the autumn L. edodes is obtained as powder; hence, it is necessary to develop a processing method to utilize its flavor and aroma at an affordable price. Additionally, we estimated the content of 𝛽-glucan, ergosterol, vitamin D₂, reducing sugars, and free amino acids and evaluated the anti-inflammatory activity of saccharification powder of log-cultivated L. edodes. In the saccharification powders obtained via 7 min of UV irradiation of log-cultivated L. edodes, 𝛽-glucan and vitamin D₂ contents were found to be the highest, whereas ergosterol content was found to be the lowest. The content of reducing sugars ranged from 62.4 mg/L to 68.2 mg/L. The free amino acids were higher in these saccharification powders than in the control. Subsequently, RAW 264.7 cells were treated with different concentrations (10, 50, 100, 200, 300, and 500 ㎍/mL) of the saccharification powders of log-cultivated L. edodes obtained via different UV irradiation time applications. The cells showed good viability; the anti-inflammatory effect was found to be the highest at 7 min UV irradiation. Therefore, 7 min of UV irradiation was determined to be the optimum condition for manufacturing saccharification powders of log-cultivated L. edodes. Hence, saccharification powders of log-cultivated L. edodes may be used as a raw material for natural sweeteners, food additives, and in the food industry.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.40 no.6
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• pp.603-611
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• 2020

This study collected and analyzed transportation card data in order to better understand the operation and usage of city buses in Ulsan Metropolitan City in Korea. The analysis used quantitative and qualitative indicators according to the characteristics of the data, and also the categories were classified as general status, operational status, and satisfaction. The existing city bus survey method has limitations in terms of survey scale and in the survey process itself, which incurs various types of errors as well as requiring a lot of time and money to conduct. In particular, the bus means indicators calculated using transportation card data were analyzed to compensate for the shortcomings of the existing operational status survey methods that rely entirely on site surveys. The city bus index calculated by using the transportation card data involves quantitative operation status data related to the user, and this results in the advantage of being able to conduct a complete survey without any data loss in the data collection process. We took the transportation card data from the entire city bus network of Ulsan Metropolitan City on Wednesday April 3, 2019. The data included information about passenger numbers/types, bus types, bus stops, branches, bus operators, transfer information, and so on. From the data analysis, it was found that a total of 234,477 people used the city bus on the one day, of whom 88.6% were adults and 11.4% were students. In addition, the stop with the most passengers boarding and alighting was Industrial Tower (10,861 people), A total of 20,909 passengers got on and off during the peak evening period of 5 PM to 7 PM, and 13,903 passengers got on and off the No. 401 bus route. In addition, the top 26 routes in terms of the highest number of passengers occupied 50% of the total passengers, and the top five bus companies carried more than 70% of passengers, while 62.46% of the total routes carried less than 500 passengers per day. Overall, it can be said that this study has great significance in that it confirmed the possibility of replacing the existing survey method by analyzing city bus use by using transportation card data for Ulsan Metropolitan City. However, due to limitations in the collection of available data, analysis was performed only on one matched data, attempts to analyze time series data were not made, and the scope of analysis was limited because of not considering a methodology for efficiently analyzing large amounts of real-time data.

• Journal of Intelligence and Information Systems
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• v.27 no.1
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• pp.177-190
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• 2021

Due to the development of the fourth industrial revolution technology, efforts are being made to improve areas that humans cannot handle by utilizing artificial intelligence techniques such as machine learning. Although on-demand production companies also want to reduce corporate risks such as delays in delivery by predicting total production time for orders, they are having difficulty predicting this because the total production time is all different for each order. The Theory of Constraints (TOC) theory was developed to find the least efficient areas to increase order throughput and reduce order total cost, but failed to provide a forecast of total production time. Order production varies from order to order due to various customer needs, so the total production time of individual orders can be measured postmortem, but it is difficult to predict in advance. The total measured production time of existing orders is also different, which has limitations that cannot be used as standard time. As a result, experienced managers rely on persimmons rather than on the use of the system, while inexperienced managers use simple management indicators (e.g., 60 days total production time for raw materials, 90 days total production time for steel plates, etc.). Too fast work instructions based on imperfections or indicators cause congestion, which leads to productivity degradation, and too late leads to increased production costs or failure to meet delivery dates due to emergency processing. Failure to meet the deadline will result in compensation for delayed compensation or adversely affect business and collection sectors. In this study, to address these problems, an entity that operates an order production system seeks to find a machine learning model that estimates the total production time of new orders. It uses orders, production, and process performance for materials used for machine learning. We compared and analyzed OLS, GLM Gamma, Extra Trees, and Random Forest algorithms as the best algorithms for estimating total production time and present the results.

• Korean Journal of Plant Resources
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• v.34 no.1
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• pp.23-30
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• 2021

Hemistepta lyrata Bunge (HL) has been used as a folk remedy to treat cancer, inflammation, bleeding, hemorrhoids and fever, and leaves and young shoots have been used as famine food. Nevertheless, the biological activities and underlying mechanisms of the anti-inflammatory effects remain unclear. In this study, it was undertaken to explore the functions of the aerial part of HL as a suppressor of inflammation by using RAW 264.7 cells. As immune response parameters, the productions of as nitric oxide (NO) and prostaglandin E2 (PGE2), cytokines such tumor necrotic factor (TNF)-α and interleukin (IL)-6 were evaluated. Although the release of TNF-α remained unchanged in HL-treated RAW 264.7 cells, the productions of NO, PGE2 and IL-6 were significantly increased at concentrations with no cytotoxicity. Furthermore, HL significantly attenuated the mitogen-activated protein kinases (MAPK) pathway including decreasing the phosphorylation of the extracellular signal-regulated kinase (ERK1/2) and p38 mitogen-activated protein kinases. Collectively, this study provides evidence that HL inhibits the production of major pro-inflammatory molecules in LPS-stimulated RAW 264.7 cells via suppression of ERK and P38 MAPK signaling pathways. These findings suggest that the beneficial therapeutic effects of HL may be attributed partly to its ability to modulate immune functions in macrophages.

• Journal of Food Hygiene and Safety
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• v.35 no.6
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• pp.544-551
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• 2020

The aim of this study was to develop and validate a simultaneous analytical method for berberine and palmatine, which are representative substances of Phellodendron amurense, and to evaluate the antioxidant activity. We evaluated the specificity, linearity, precision, accuracy, limit of detection (LOD), and limit of quantification (LOQ) of analytical methods for berberine and palmatine using high-performance liquid chromatography. Our result showed that the correlation coefficients of the calibration curve for berberine and palmatine exhibited 0.9999. The LODs for berberine and palmatine were 0.32 to 0.35 µg/mL and the LOQs were 0.97 to 1.06 µg/mL, respectively. The inter-day and intra-day precision values for berberine and palmatine were from 0.12 to 1.93 and 0.19 to 2.89%, respectively. The inter-day and intra-day accuracies were 98.43-101.45% and 92.39-100.60%, respectively. In addition, the simultaneous analytical method was validated for the detection of berberine and palmatine. Moreover, we conducted FRAP and NaNO2 scavenging activity assays to measure the antioxidant activities of berberine and palmatine, and both showed antioxidant activity. These results suggest that P.amurense could be a potential natural resource for antioxidant activity and that the efficacy can be confirmed by investigating the content of the berberine and palmatine.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.66 no.4
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• pp.419-427
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• 2021

In South Korea, direct seeding of rapeseed (Brassica napus L.) is difficult during spring cultivation in early March because of the low yield production associated with late flowering and poor seed quality. To compare the period of direct sowing, the present study investigated the growth characteristics of rapeseed according to planting dates. Specifically, 35 day-old seedlings were transplanted or directly sown on four different dates (late February, early March, late March, and early April) in 2020 and 2021. As the planting date was delayed, the days to flowering of rapeseed decreased. Similarly, the plant height, seed set percentage, and seed yield of rapeseed were reduced upon delay in planting. The seed yield of rapeseed through direct seeding in late February was the highest, 2.76 ton·ha^-1. On all seeding dates, except for late February, the transplanted rapeseed produced a higher yields than the directly seeded rapeseed. The crude oil and oleic acid content, which is related to the quality of rapeseed, decreased with the delay in planting dates, and this decrease was greater, with the direct seeding of rapeseed depending on the sowing time. In the correlation analysis, the planting date was significantly and negatively correlated with the yield, crude oil content, and oleic acid content of the transplanted rapeseed, while the sowing date was negatively correlated with the plant height, silique size, yield, and seed quality of the directly seeded rapeseed. Finally, the effect of planting date on rapeseed growth was stronger in direct seeding than in transplanting. Therefore, during spring cultivation after late February to early March, transplanting, rather than direct seeding, in more advantageous in terms of seed quality and yield.

• Journal of the Economic Geographical Society of Korea
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• v.25 no.1
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• pp.109-130
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• 2022

The Vietnamese government has proposed contract farming through a new type of cooperative as an institutional innovation which aims to restructure the agricultural sector. However, policy changes often impact farmers, who bear the primary effects of the transition process. Understanding households' strategies for land use and livelihood is crucial for policymaking in the agricultural development field. This study was conducted in the rural Binh Dao commune in Central Vietnam. We analyzed household members' labor force changes and their livelihood behaviors after their participation in a contract farming scheme using qualitative analysis methods combined with geographic information system (GIS) support, based on secondary data and in-depth interviews of 190 farmers. Simultaneously, we created a digital map of the cooperative's production area to investigate changes in land use and production activities. The findings show that contract farming shaped the vertical coordination of the value chain from the farmers to the cooperative and agricultural product trading companies. Subsequently, it encouraged land use and labor efficiency due to mechanical support. In addition, it also increased productivity and protected farmers from market risks. However, despite its positive effects on agricultural productivity in this case, the contract farming scheme could not achieve the restructuring of the rural labor force toward non-agricultural sectors. Ironically, farmers in the Binh Dao commune tended to increase cultivable land during the agricultural restructuring program, rather than switching their labor forces to non-agricultural sectors. The lack of stable non-farming job opportunities in rural Vietnam results in challenges to the efficiency of agricultural restructuring programs. Consequently, farmers in the Binh Dao commune are still smallholder farmers, depending on the family labor force.

• Journal of Navigation and Port Research
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• v.46 no.3
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• pp.179-190
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• 2022

In this study, we investigated the characteristic impedance and bandwidth of CPW3DCS (coplanar waveguide employing periodic 3D coupling structures), and examined its potential for the development of a marine radio communication FISoC (fully-integrated system on chip) semiconductor device. To extract bandwidth and characteristic impedance of the CPW3DC, we induced a measurement-based equation reflecting measured insertion loss, and compared the measured results of the propagation constant β and characteristic impedance with the measured ones. According to the results of the comparison, the calculated results show a good agreement with the measured ones. Concretely, the propagation constant β and characteristic impedance exhibited an maximum error of 3.9% and 6.4%, respectively. According to the results of this study, in a range of LT = 30 ~ 150 ㎛ for the length of periodic structures, the CPW3DC exhibited a passband characteristic of 121 GHz, and a very small dependency of characteristic impedance on frequency. We could realize a low impedance transmission line with a characteristic impedance lower than 20 Ω by using CPW3DCS with a line width of 20 ㎛, which was highly reduced, compared with a 3mm line width of conventional transmission line with the same impedance. The characteristic impedance was easily adjusted by changing LT. The above results indicate that the CPW3DC can be usefully used for the development of a wireless communication FISoC (fully-integrated system on chip) semiconductor device. This is the first report of a study on the bandwidth of the CPW3DC.