• Journal of Mushroom
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• v.19 no.1
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• pp.23-32
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• 2021

This study investigated the anti-hyperlipidemic and anti-obesity effects of Sparassis latifolia (S. latifolia) fruiting body powder in rats fed with a high fat and cholesterol diet (HFD). Rats were fed a normal control diet (ND), an HFD, an HFD supplemented with 5% fruiting body powder of S. latifolia (HFD+SL), or an HFD supplemented with 0.03% simvastatin (HFD+SS), for 6 weeks. The HFD group demonstrated considerable increase in body weight gain, the food efficiency ratio (FER), and plasma cholesterol and triglyceride levels, compared to the ND group. In contrast, the HFD+SL and HFD+SS groups showed significantly reduced body weight gain, food intake, and plasma cholesterol and triglyceride levels compared to the HFD group. In particular, the HFD+SL and HFD+SS diets significantly suppressed the occurrence of non-alcoholic fat deposits in the liver. Taken together, these results suggest that dietary supplementation of the fruiting body powder of S. latifolia in an HFD could lower the risks of hyperlipidemia, atherogenesis, and obesity and may be used as a functional food to manage cardiovascular disease and fecal lipid and cholesterol levels.

• 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.617-634
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• 2020

The purpose of this study is to investigate the relationship of between earthquakes and fluctuation of water level in a groundwater well of the active-fault zone and 124 national groundwater monitoring wells in Gyeongju area. The spatial and temporal relationships between the fluctuation of water level and the earthquake were analyzed by the calculation of earthquake effectiveness (ε) and q-factor which are the function of earthquake magnitude and distance from epicenter. Two earthquake events of E1 (April 22, 2019, M 3.8) and E2 (June 11, 2019, M 2.5) show a close relationship with a post-seismic 83 cm decrease and a pre-seismic 76 cm increase in water level at the active fault zone of Dangu-ri, respectively. The spatial analysis of water level fluctuation data in National Groundwater Monitoring Networks caused by earthquake events shows a more distinct response in deep groundwater around fault zones than other area, and a greater change in deep groundwater than shallow groundwater. It's inferred that the decrease and increase in groundwater level are affected by the expansion of fractures and compression of rock mass due to seismic stress, respectively. The effective ranges of ε-value and q-factor of the monitoring well in Dangu-ri were calculated as 2.70E-10~5.60E-10 and 14.4~18.0, respectively.

• 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.

• The Journal of Engineering Geology
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• v.30 no.4
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• pp.469-483
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• 2020

The results of long-term groundwater level and quality monitoring can be used not only as the basic data for evaluating the impact of various disasters including climate change and establishing responses, but also as key data for predicting and managing geological disasters such as earthquakes. Some countries use groundwater level and quality monitoring for researches to predict earthquakes and to assess the impacts of the earthquake disaster. However, a few cases in Korea report on individual groundwater quality factors (i.e., dissolved ions) observed before and after the earthquakes, being different from other countries. To establish the abnormality criteria for groundwater quality in Pohang, groundwater samples were collected and analyzed five times from 14 agricultural or private wells existing in Shingwang-myeon and Heunghae-eup. As a result of the analysis, it was found that Ca2+ was the dominant cation in Shingwang-myeon, while Na+ was the dominant cation in Heunghae-eup. The elevated NO3- concentration in Shingwang-myeon is contributed to the agricultural activity in the area. A high concentration of Fe was detected in a well on Heunghae-eup; the concentration exceeded the drinking water standard by nearly 100 times. Relatively higher dissolved ions were observed in the groundwater of Heunghae-eup, and it is considered as the result of the flow velocity difference and water-rock reaction accompanying the difference in bedrock and sediment characteristics. The groundwater of Shingwang-myeon appeared to be most affected by the weathering of granite and silicates, while that of Heunghae-eup was mainly affected by the weathering of silicates and carbonate. The background concentrations (baselines) of groundwater Shingwang-myeon and Heunghae-eup was identified through the survey; however, the continuous monitoring is required to monitor the possible changes and the repeatability of seasonal variation.

• Korean Journal of Poultry Science
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• v.48 no.1
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• pp.13-22
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• 2021

The present experiment was conducted to evaluate the effect of stocking density on the growth performance, immune status, and meat quality of broilers. In total, 385 one-day-old Ross 308 broilers were randomly assigned to one of four distinct stocking densities: 26 birds/㎡, 22 birds/㎡, 19 birds/㎡, and 16 birds/㎡. They were fed the diet ad libitum for 5 weeks. Immunoglobulin (Ig) and corticosterone levels were evaluated, and growth performance, blood parameters, and breast meat quality were determined. It was observed that the weight gain and feed intake of growers (21~35 d) and broilers (0~35 d) were significantly reduced as the stocking density increased (P<0.05). However, the feed intake of starters (0~21 d) significantly increased as the stocking density increased (P<0.05). There were no significant differences in the biochemical profiles among the four different stock densities. Furthermore, no significant differences were observed in the stress parameters: (heterophils / lymphocytes ratio and corticosterone), IgA, and IgM; however, IgG significantly increased with stocking density (P<0.05). The pH, water holding capacity, and cooking loss of the muscle were all unaffected by the stocking density, but the shear force (tenderness) increased slightly as the density increased. The findings of this study suggest that a lower stocking density (16 birds/㎡) significantly improved the shear force of breast meat and IgG in broilers.

• 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.

• Korean Journal of Agricultural and Forest Meteorology
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• v.22 no.4
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• pp.268-278
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• 2020

Flowering time has been put forward due to the recent abnormally warm winter, which often caused damages of flower buds by late frosts persistently. In the present study, cumulative chill unit and cumulative heat unit of Niitaka pear, which are required for releasing the endogenous dormancy and for flowering after breaking dormancy, respectively, were compared between flowering time prediction models used in South K orea. Observation weather data were collected at eight locations for the recent three years from 2018-2020. The dates of full bloom were also collected to determine the confidence level of models including DVR, mDVR and CD models. It was found that mDVR model tended to have smaller values (8.4%) of the coefficient of variation (cv) of chill units than any other models. The CD model tended to have a low value of cv (17.5%) for calculation of heat unit required to reach flowering after breaking dormancy. The mDVR model had the most accurate prediction of full bloom during the study period compared with the other models. The DVR model usually had poor skills in prediction of full bloom dates. In particular, the error of the DVR model was large especially in southern coastal areas (e.g., Ulju and Sacheon) where the temperature was warm. Our results indicated that the mDVR model had relatively consistent accuracy in prediction of full bloom dates over region and years of interest. When observation data for full bloom date are compiled for an extended period, the full bloom date can be predicted with greater accuracy improving the mDVR model further.

• The Journal of Korean Academy of Prosthodontics
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• v.59 no.1
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• pp.27-35
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• 2021

Purpose: The purpose of this study is to compare the accuracy of digital scans of implants according to different shapes of scanbodies, and to compare the accuracy of library merging according to different oral exposure height. Materials and methods: A master model with a single tooth edentulous site was prepared. For the first experiment, three types of intraoral scanbodies were prepared, divided into three groups, and the following experiments were conducted for each group: An internal hex implant was placed. The master model with the scanbody connected was scanned with a model scanner, and a master reference file (control group) was created. 10 files (experimental group) were created by performing 10 consecutive scans with an intraoral scanner. After superimposing the control and experimental groups, the following values were calculated: 1) Distance deviation of a designated point on the scanbody 2) Angle deviation of the major axis of the scanbody. For the second experiment, the scanbody scan data were prepared in 6 different heights. Library files were merged with each of the scan data. The distance and angular deviation were calculated using the 7 mm scan data as control group. Results: In the first experiment, there were no significant differences between A and B (P=.278), B and C (P=.568), and C and A (P=.711) in the distance deviations. There were no significant differences between A and B (P=.568), B and C (P=.546), and C and A (P=.112) in the angular deviations. Also, the scanbody showed significantly higher library merging accuracy in the groups with high oral exposure height (P<.5). Conclusion: There were no significant differences in scan accuracy according to the different shapes of scanbodies, and the accuracy of library merging increased according to exposure height of the scanbody in the oral cavity.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.66 no.1
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• pp.97-104
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• 2021

This research examined the effects of different liquid manure based anaerobic digestate on the growth and yield of rice compared to chemical fertilizer. The liquid manure was produced by aerobic fermentation from swine with cow or apple pomace anaerobic digestate and treated at different concentrations. The number of grains per panicle increased in both the liquid manure-treated and chemical fertilizer treated rice. The yield index did not vary significantly between the liquid manure and chemical fertilizer. An increased concentration of liquid manure did not correlate with increases in unhulled rice. However, pH and exchangeable K in the soil increased with an increase in liquid manure. In summary, we suggest a properly applied 100% liquid manure fertilizer can replace chemical fertilizer to reduce our excessive use of inorganic fertilizer.