• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.2D
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• pp.299-309
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• 2006

Railway noise and vibration has been recognized as major problems with the speed-up of rolling stock. As a kind of solution to these problems, the decrease of stiffness of track pad have been tried. However, in this case, overturning of rail due to lateral force should be considered because it can have effect on the safety of running train. Therefore, above two things - decrease of stiffness of track pad and overturning of rail due to lateral force - should be considered simultaneously for the appropriate determination of spring coefficient of track pad. With this viewpoint, minimum spring coefficient of track pad is estimated through the comparison between the theoretical relationship about the overturning of rail and 3-dimensional FE analysis result. Two kinds of Lateral force and wheel load are used as input loads. Extracted values from the conventional estimation formula and the Shinkansen design loads are used. It is found that the overturning of rail changes corresponding to the change of the stiffness of track pad and the ratio of lateral force to wheel load. Moreover, it is found that the analysis model can have influence on the results. Through these procedure, minimum spring coefficient of track pad is estimated.

• Geophysics and Geophysical Exploration
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• v.26 no.4
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• pp.171-184
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• 2023

Machine learning (ML)-based cavity detection using a large amount of survey data obtained from vehicle-mounted ground penetrating radar (GPR) has been actively studied to identify underground cavities. However, only simple image processing techniques have been used for preprocessing the ML input, and many conventional seismic and GPR data processing techniques, which have been used for decades, have not been fully exploited. In this study, based on the idea that a cavity can be identified using diffraction, we applied ML-based diffraction separation to GPR data to increase the accuracy of cavity detection using the YOLO v5 model. The original ML-based seismic diffraction separation technique was modified, and the separated diffraction image was used as the input to train the cavity detection model. The performance of the proposed method was verified using public GPR data released by the Seoul Metropolitan Government. Underground cavities and objects were more accurately detected using separated diffraction images. In the future, the proposed method can be useful in various fields in which GPR surveys are used.

• Korean Journal of Agricultural Science
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• v.14 no.1
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• pp.164-185
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• 1987

The Korean economy has been developed rapidly in the course of implementing the five year economic development plans since 1962. Accordingly the industrial and employment structure have been changed from the traditional agriculture to modem industrial economy. In the course of implementing export oriented industrialization policies, rural farm economy has been encountered labour shortage owing to rural farm population drain to urban areas, rural wage hike and pressure on farm operation costs, and possibility of farm productivity decrease. To cope with the above problems the Korean government has supplied farm machinery such as power tillers, tractors, transplanters, binders, combines, dryers and etc. by means of the favorable credit support and subsidies. The main objectives of this study are to identify the investment effects of farm mechanization such as B/C and Internal Rate of Return by machinery and operation patterns, changes of labour requirement per 10a for rice culture since 1965, partial farm budget of rice with and without mechanization, and estimation labour input with full mechanization. To achieve the objectives Saemaeul farm mechanization groups, common ownership and operation, and farms with private ownership and operation were surveyed mainly in Nonsan granary area, Chungnam province. The results of this study are as follows 1. The national average of labor input per 10a of paddy has decreased from 150.1Hr in 1965 to 87.2Hr in 1985 which showes 42% decrease of labour inputs. On the other hand the hours of labour input in Nonsan area have also decreased from 150.1Hr to 92.8Hr, 38% of that in 1965, during the same periods. 2. The possible labor saving hours per 10a of Paddy was estimated at 60 hours by substituting machine power for labor forces in the works of plowing, puddling, transplanting, harvesting and threshing, transporting and drying The labor savings were derived from 92.8 hours in 1986 deducting 30 hours of labor input with full mechanization in Nonsan area. 3. Social benefits of farm mechanization were estimated at 124,734won/10a including increment of rice (10%): 34,064won,labour saving: 65,800won,savings of conventional farm implements: 18,000 won and savings of animal power: 6,870won. 4. Rental charges by works prevailing in the area were 12,000won for land preparation, 15,000won for transplanting with seedlings, 19,500won for combine works and 6,000won for drying paddy. 5. Farm income per 10a of paddy with and without mechanization were amounted to 247,278won and 224,768won respectively. 6. Social rate of return of the machinery were estimated at more than 50% in all operation patterns. On the other hand internal rate of return of the machinery except tractors were also more than 50% but IRR of tractors by operation patterns were equivalent to 0 to 9%. From the view point of farmers financial status, private owner-operation of tractors is considered uneconomical. Tractor operation by Saemaeul mechanization groups would be economical considering the government subsidy, 40% of tractor price. 7. Farmers recommendations for the government that gained through field operation of farm machinery are to train maintenance technology for rural youth, to standardize the necessary parts of machinery, to implement price tag system, to intercede spare parts and provide marketing information to farmers by rural institutions as RDA,NACF,GUN office and FLIA.

• Tunnel and Underground Space
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• v.31 no.5
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• pp.374-384
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• 2021

In this study, we propose a new approach for automatic fracture detection in CT scan images of rock specimens. This approach is built on top of two-stage object detection deep learning algorithm called Faster R-CNN with a major modification of using rotated bounding box. The use of rotated bounding box plays a key role in the future work to overcome several inherent difficulties of fracture segmentation relating to the heterogeneity of uninterested background (i.e., minerals) and the variation in size and shape of fracture. Comparing to the commonly used bounding box (i.e., axis-align bounding box), rotated bounding box shows a greater adaptability to fit with the elongated shape of fracture, such that minimizing the ratio of background within the bounding box. Besides, an additional benefit of rotated bounding box is that it can provide relative information on the orientation and length of fracture without the further segmentation and measurement step. To validate the applicability of the proposed approach, we train and test our approach with a number of CT image sets of fractured granite specimens with highly heterogeneous background and other rocks such as sandstone and shale. The result demonstrates that our approach can lead to the encouraging results on fracture detection with the mean average precision (mAP) up to 0.89 and also outperform the conventional approach in terms of background-to-object ratio within the bounding box.

• Journal of Internet Computing and Services
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• v.14 no.5
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• pp.69-76
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• 2013

The incidence of globally infectious and pathogenic diseases such as H1N1 (swine flu) and Avian Influenza (AI) has recently increased. An infectious disease is a pathogen-caused disease, which can be passed from the infected person to the susceptible host. Pathogens of infectious diseases, which are bacillus, spirochaeta, rickettsia, virus, fungus, and parasite, etc., cause various symptoms such as respiratory disease, gastrointestinal disease, liver disease, and acute febrile illness. They can be spread through various means such as food, water, insect, breathing and contact with other persons. Recently, most countries around the world use a mathematical model to predict and prepare for the spread of infectious diseases. In a modern society, however, infectious diseases are spread in a fast and complicated manner because of rapid development of transportation (both ground and underground). Therefore, we do not have enough time to predict the fast spreading and complicated infectious diseases. Therefore, new system, which can prevent the spread of infectious diseases by predicting its pathway, needs to be developed. In this study, to solve this kind of problem, an integrated monitoring system, which can track and predict the pathway of infectious diseases for its realtime monitoring and control, is developed. This system is implemented based on the conventional mathematical model called by 'Susceptible-Infectious-Recovered (SIR) Model.' The proposed model has characteristics that both inter- and intra-city modes of transportation to express interpersonal contact (i.e., migration flow) are considered. They include the means of transportation such as bus, train, car and airplane. Also, modified real data according to the geographical characteristics of Korea are employed to reflect realistic circumstances of possible disease spreading in Korea. We can predict where and when vaccination needs to be performed by parameters control in this model. The simulation includes several assumptions and scenarios. Using the data of Statistics Korea, five major cities, which are assumed to have the most population migration have been chosen; Seoul, Incheon (Incheon International Airport), Gangneung, Pyeongchang and Wonju. It was assumed that the cities were connected in one network, and infectious disease was spread through denoted transportation methods only. In terms of traffic volume, daily traffic volume was obtained from Korean Statistical Information Service (KOSIS). In addition, the population of each city was acquired from Statistics Korea. Moreover, data on H1N1 (swine flu) were provided by Korea Centers for Disease Control and Prevention, and air transport statistics were obtained from Aeronautical Information Portal System. As mentioned above, daily traffic volume, population statistics, H1N1 (swine flu) and air transport statistics data have been adjusted in consideration of the current conditions in Korea and several realistic assumptions and scenarios. Three scenarios (occurrence of H1N1 in Incheon International Airport, not-vaccinated in all cities and vaccinated in Seoul and Pyeongchang respectively) were simulated, and the number of days taken for the number of the infected to reach its peak and proportion of Infectious (I) were compared. According to the simulation, the number of days was the fastest in Seoul with 37 days and the slowest in Pyeongchang with 43 days when vaccination was not considered. In terms of the proportion of I, Seoul was the highest while Pyeongchang was the lowest. When they were vaccinated in Seoul, the number of days taken for the number of the infected to reach at its peak was the fastest in Seoul with 37 days and the slowest in Pyeongchang with 43 days. In terms of the proportion of I, Gangneung was the highest while Pyeongchang was the lowest. When they were vaccinated in Pyeongchang, the number of days was the fastest in Seoul with 37 days and the slowest in Pyeongchang with 43 days. In terms of the proportion of I, Gangneung was the highest while Pyeongchang was the lowest. Based on the results above, it has been confirmed that H1N1, upon the first occurrence, is proportionally spread by the traffic volume in each city. Because the infection pathway is different by the traffic volume in each city, therefore, it is possible to come up with a preventive measurement against infectious disease by tracking and predicting its pathway through the analysis of traffic volume.