• Korean Journal of Remote Sensing
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• v.36 no.5_1
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• pp.823-833
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• 2020

In order to stably produce crops, there is an increasing demand for effective crop monitoring techniques in domestic agricultural areas. In this manuscript, a cultivation area extraction method by using deep learning model is developed, and then, applied to satellite imagery. Training dataset for crop cultivation areas were generated using RapidEye satellite images that include blue, green, red, red-edge, and NIR bands useful for vegetation and environmental analysis, and using this, we tried to estimate the crop cultivation area of onion and garlic by deep learning model. In order to training the model, atmospheric-corrected RapidEye satellite images were used, and then, a deep learning model using FC-DenseNet, which is one of the representative deep learning models for semantic segmentation, was created. The final crop cultivation area was determined as object-based data through combination with cadastral maps. As a result of the experiment, it was confirmed that the FC-DenseNet model learned using atmospheric-corrected training data can effectively detect crop cultivation areas.

• Journal of the Korean Society of Groundwater Environment
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• v.3 no.2
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• pp.51-59
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• 1996

In case waste disposal site is to be constructed close to the underground facilities such as LPG storage cavern which is completely maintained by groundwater pressure, it is generally requested that the possibility on leachate contamination of cavern area be reviewed and the countermeasure, if it is estimated cavern area is severely affected by leachate, be taken into consideration. Prediction was performed and leachate control plan was made using by analytical and the numerical analysis on the leachate migration which is likely to happen at the area between the proposed waste disposal site and the underground LPG storage cavern located at the U petrochemical complex. Analytical solutions were obtained by the conservative mass advection-diffusion equation and the effect of advection and dispersion factor on the leachate migration was reviewed through peclet number calculation and the functional relationship between the factors and leachate transport velocity was established, which leads to enable us to predict the leachate transport velocity without difficulties when different parameters (factors) are used for analytical solution. Numerical solutions were obtained by FEM using AQUA2D which is for the simulation of groundwater flow and contaminant transport. 3-D discrete fracture models were simulated and fracture flow analysis was performed and feasibility study on the water-curtain system was conducted through the fracture connectivity analysis in rock mass. As results of those analyses, it was interpreted that the leachate would trespass on the LPG storage cavern area in 30 years from the proposed wate disposal site and the vertical water-curtain system was effective mathod for the prevention of leachate's migration further into the cavern area.

• Journal of Korean Society of Transportation
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• v.30 no.4
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• pp.95-106
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• 2012

Driver's capability of identifying the change in freeway alignments and environments is one of important factors associated with traffic safety on freeways. In particular, driver's visibility and recognition capability are highly dependent on the altitude of the sun by sunset, sunrise, and nighttime. The purpose of this study is to identify the characteristics of geometric conditions affecting crash occurrences at sunset, sunrise, and nighttime. Poisson and negative binomial regressions were adopted to predict freeway crash frequency in this study. Freeway crash data during 2007~2010 were used for developing the crash frequency models. A set of variables representing the characteristics of geometric conditions were identified as significant ones affecting crash occurrences. The results of this study would be useful in deriving effective countermeasures for preventing traffic crashes that mainly occur at sunset, sunrise, and nighttime on freeways.

• Economic and Environmental Geology
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• v.45 no.6
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• pp.697-707
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• 2012

The quantitative landslide susceptibility assessment methods can be divided into statistical approaches and geomechanical approaches based on the consideration of the triggering factors and landslide models. The geomechanical approach is considered as one of the most effective approaches since this approach proposes physical slope model and considers geomorphological and geomechanical properties of slope materials. Therefore, the geomechanical approaches has been used widely in landslide susceptibility analysis using the infinite slope model as physical slope model. However, the previous studies assumed constant groundwater level for broad study area without the consideration of rainfall intensity and hydraulic properties of soil materials. Therefore, in this study, landslide susceptibility assessment was implemented using the coupled infinite slope model with hydrologic model. For the analysis, geomechanical and hydrualic properties of slope materials and rainfall intensity were measured from the soil samples which were obtained from field investigation. For the practical application, the proposed approach was applied to Jinbu area, Gangwon-Do which was experienced large amount of landslides in July 2006. In order to compare to the proposed approach, the previous approach was used to analyze the landslide susceptibility using randomly selected groundwater level. Comparison of the results shows that the accuracy of the proposed method was improved with the consideration of the hydrologic model.

• Journal of The Korean Society of Agricultural Engineers
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• v.60 no.6
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• pp.43-54
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• 2018

The accurate estimation of reference crop evapotranspiration ($ET_o$) is essential in irrigation water management to assess the time-dependent status of crop water use and irrigation scheduling. The importance of $ET_o$ has resulted in many direct and indirect methods to approximate its value and include pan evaporation, meteorological-based estimations, lysimetry, soil moisture depletion, and soil water balance equations. Artificial neural networks (ANNs) have been intensively implemented for process-based hydrologic modeling due to their superior performance using nonlinear modeling, pattern recognition, and classification. This study adapted two well-known ANN algorithms, Backpropagation neural network (BPNN) and Generalized regression neural network (GRNN), to evaluate their capability to accurately predict $ET_o$ using daily meteorological data. All data were obtained from two automated weather stations (Chupungryeong and Jangsu) located in the Yeongdong-gun (2002-2017) and Jangsu-gun (1988-2017), respectively. Daily $ET_o$ was calculated using the Penman-Monteith equation as the benchmark method. These calculated values of $ET_o$ and corresponding meteorological data were separated into training, validation and test datasets. The performance of each ANN algorithm was evaluated against $ET_o$ calculated from the benchmark method and multiple linear regression (MLR) model. The overall results showed that the BPNN algorithm performed best followed by the MLR and GRNN in a statistical sense and this could contribute to provide valuable information to farmers, water managers and policy makers for effective agricultural water governance.

• Archives of design research
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• v.19 no.5 s.67
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• pp.55-64
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• 2006

As digital systems were introduced to automotive design in the mid 1980s, the design process has adopted many digital programs to save time compared to the conventional hand drafting. Digital technology was introduced not only to satisfy the reeds of the global environment, as the number of automobiles exported to many different parts of the world has increased, but also to save time and effort in developing several models of quality automobiles. Therefore, every automotive manufacturer in the world has expanded its virtual reality(VR) studio to establish visualization systems that visualize automobiles in the actual size and a co-operation system that enables simultaneous feedback from all of its design studios around the world. Unlike the existing design reviewing methos, the new improved feedback system is assessed as a reasonable method to evaluates and understand how the automobiles are actually manufactured in simulation. It is especially helpful when advanced products and concept cars require fast results. Other strengths of the new system include shorter development period, cost efficiency, no more manual labor, various designs within a short period of time, and realistic visualization of concepts. Large-scale products, including automobiles, need to be projected in the actual size and high clarity through the Power-wall System and are examined in a virtual space called a Cave. Therefore, it took much time to establish digital infrastructure. An infrastructure would constantly require system improvement and performance enhancement, but it is certain that now is the right time for the take-off to utilizing the strengths of digital design and improve the weaknesses. In this respect, this study provided an understanding of the importance of digital design based on digital reinforcements and examined an effective utilization of digital technology for an efficient development of automobiles in the future.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.5
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• pp.1-6
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• 2020

UAV (Unmanned Aerial Vehicles) are used widely for military purposes because they are more economical than general manned aircraft and satellites, and have easy access to the object. Recently, owing to the development of IT technology, UAV equipped with various sensors have been released, and their use is increasing in a wide range of fields, such as surveying, agriculture, meteorological observation, communication, broadcasting, and sports. An increasing number of studies and attempts have made use of it. On the other hand, existing research was related mostly to photogrammetry, but there has been a lack of analytical research on LiDAR (Light Detection And Ranging). Therefore, this study examined the characteristics of a UAV LiDAR sensor for the application of a geospatial information field. In this study, the performance of commercialized LiDAR sensors, such as the acquisition speed and the number of echoes, was investigated, and data acquisition and analysis were conducted by selecting Surveyor Ultra and VX15 models with similar accuracy and data acquisition distances. As a result, a DSM of each study site was generated for each sensor, and the characteristics of data density, precision, and acquisition of ground data from vegetation areas were presented through comparison. In addition, the UAV LiDAR sensor showed an accuracy of 0.03m ~ 0.05m. Hence, it is necessary to select equipment considering the characteristics of data for effective use. In the future, the use of UAV LiDAR may be suggested if additional data can be obtained and analyzed for various areas, such as urban areas and forest areas.

• Journal of KIISE:Computer Systems and Theory
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• v.36 no.4
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• pp.274-282
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• 2009

Various location tracking sensors; such as GPS, INS, radar, and optical equipment; are used for tracking moving targets. In order to effectively track moving targets, it is necessary to develop an effective fusion method for these heterogeneous devices. There have been studies in which the estimated values of each sensors were regarded as different models and fused together, considering the different error characteristics of the sensors for the improvement of tracking performance using heterogeneous multi-sensor. However, the rate of errors for the estimated values of other sensors has increased, in that there has been a sharp increase in sensor errors and the attempts to change the estimated sensor values for the Sensor Probability could not be applied in real time. In this study, the Sensor Probability is obtained by comparing the RMSE (Root Mean Square Error) for the difference between the updated and measured values of the Kalman filter for each sensor. The process of substituting the new combined values for the Kalman filter input values for each sensor is excluded. There are improvements in both the real-time application of estimated sensor values, and the tracking performance for the areas in which the sensor performance has rapidly decreased. The proposed algorithm adds the error characteristic of each sensor as a conditional probability value, and ensures greater accuracy by performing the track fusion with the sensors with the most reliable performance. The trajectory of a UAV is generated in an experiment and a performance analysis is conducted with other fusion algorithms.

• Asian-Australasian Journal of Animal Sciences
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• v.25 no.2
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• pp.151-162
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• 2012

Analysis for back fat thickness (BFAT) and daily body weight gains from birth to the end of a performance test were conducted to find an optimal method for estimation of weaning age effects and to ascertain impacts of weaning age on the growth performance of purebred Berkshire pigs from a closed population in Korea. Individual body weights were measured at birth (B), at weaning (W: mean, 22.9 d), at the beginning of the performance test (P: mean, 72.7 d), and at the end of the performance test (T: mean, 152.4 d). Further, the average daily gains in body weight (ADG) of 3,713 pigs were analyzed for the following periods: B to W (DGBW), W to P (DGWP), P to T (DGPT), B to P (DGBP), B to T (DGBT), and W to T (DGWT). Weaning ages ranged from 17 to 34 d, and were treated as fixed (WF), random with (WC) and random without (WU) consideration of an empirical relationship between weaning ages in the models. WF and WC produced the lowest AIC (Akaike Information Criterion) and least fractions of error variance components in multi-traits analysis, respectively. The fractions of variances due to diverse weaning age and the weaning age correlations among ADGs of different stages (when no overlapping allowed) by WC ranged from 0.09 to 0.35 and from -0.03 to 0.44, respectively. The maximum weaning age effects and optimal back fat thicknesses were attained at weaning ages of 27 to 32 d. With the exception of DGBW, the effects of weaning age on the ADGs increased (ranging from 1.50 g/d to 7.14 g/d) with increased weaning age. In addition, BFAT was reduced by 0.106 mm per increased day in weaning age. In conclusion, WC produced reasonable weaning age correlations, and improved the fitness of the model. Weaning age was one of crucial factors (comparable with heritability) influencing growth performance in Berkshire pigs. Further, these studies suggest that increasing weaning age up to 32 d can be an effective management strategy to improve growth performance. However, additional investigations of the costs and losses related to extension of the suckling period and on the extended range of weaning age are necessary to determine the productivity and safety of this practice in a commercial herd and production system.

• Asian Pacific Journal of Cancer Prevention
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• v.15 no.1
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• pp.489-494
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• 2014

Background: Psychiatric patients appear to be at lower risk of cancer. Some antipsychotic drugs might have inhibitory effects on tumor growth, including penfluridol, a strong agent. To test this, we conducted a study to determine whether penfluridol exerts cytotoxic effects on tumor cells and, if so, to explore its anti-tumor mechanisms. Methods: Growth inhibition of mouse cancer cell lines by penfluridol was determined using the 3-(4, 5-dimethylthiazol-2-yl)-2, 5-diphenyltetrazolium bromide (MTT) assay. Cytotoxic activity was determined by clonogenic cell survival and trypan blue assays. Animal tumor models of these cancer cells were established and to evaluate penfluridol for its anti-tumor efficacy in vivo. Unesterified cholesterol in cancer cells was examined by filipin staining. Serum total cholesterol and tumor total cholesterol were detected using the cholesterol oxidase/p-aminophenazone (CHOD-PAP) method. Results: Penfluridol inhibited the proliferation of B16 melanoma (B16/F10), LL/2 lung carcinoma (LL/2), CT26 colon carcinoma (CT26) and 4T1 breast cancer (4T1) cells in vitro. In vivo penfluridol was particularly effective at inhibiting LL/2 lung tumor growth, and obviously prolonged the survival time of mice bearing LL/2 lung tumors implanted subcutaneously. Accumulated unesterified cholesterol was found in all of the cancer cells treated with penfluridol, and this effect was most evident in LL/2, 4T1 and CT26 cells. No significant difference in serum cholesterol levels was found between the normal saline-treated mice and the penfluridol-treated mice. However, a dose-dependent decrease of total cholesterol in tumor tissues was observed in penfluridol-treated mice, which was most evident in B16/F10-, LL/2-, and 4T1-tumor-bearing mice. Conclusion: Our results suggested that penfluridol is not only cytotoxic to cancer cells in vitro but can also inhibit tumor growth in vivo. Dysregulation of cholesterol homeostasis by penfluridol may be involved in its anti-tumor mechanisms.