• The Journal of Engineering Geology
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• v.3 no.3
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• pp.279-293
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• 1993

In recent yeaes, the collapses of man made structures have been encountered from time to time due to the deformation of the ground in korea. Furthermore, the possibilities of casasters from the ground deformation suCh as landslide and active fault are atrracting our attention to the deformation monitoring. In this study, two-coordinate tilt which was monitored during six months in order to develop tediniques for prevention of disasters from the ground deformation. The two-coordinate tilt which was detected by a tilt-sensor installed in shallow depth on the slope with the sensitivity of 0.0001 arc.sec in every 10 minutes was recorded continously to PC through the interface with 200-m line coonection. The observed digital tilt data. together with the relevant meteorological data were analyzed in reference to engineering application. During the whole observation period of six months, the net tilt is 10.06 arc.sec to the west and 73.88 arc.sec to the south. Consequently the ground has a tilt of 74.56 arc.sec to the direction of $S7.75^{\circ}W$ with average tilting of 0.02 arc.sec/hour. In spite of such fast and large tilting, it is interpreted in view of engineering aspects that the site is much safe from danger, since both East-West and North-South components of tilt converge as time goes by. Two categories of deformational events are recognized ; one is toward the direction of surface slope and the other is to the direction of increased pore pressure. Tiks are acenain to have a close relation with precipitation of rain. The daily variation of two-coordinate tilt is delayed 4.3 hours in average after the variation of atmospheric temperature. A certain correlation between atmospheric pressure and deformation might be revealed.

• Journal of the Korea Society of Computer and Information
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• v.15 no.9
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• pp.57-65
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• 2010

This paper describes the method of efficient container number recognition in colored container image with number plate at ATC(Automatic Transfer Crane) in container terminal yard. At the Sinseondae terminal gate in Busan, the container number recognition system is installed by "intelligent port-logistics system technology development", that is government research and development project. It is the method that it sets up the tunnel structure inside camera on the gate and it recognizes the container number in order to recognize the export container cargo automatically. However, as the automation equipment is introduced to the container terminal and the unmanned of a task is gradually accomplished, the container number recognition system for the confirmation of the object of work is required at ATC in container terminal yard. Therefore, the container number recognition system fitted for it is necessary for ATC in container terminal yard in which there are many intrusive of the character recognition through image including a sunlight, rain, snow, shadow, and etc. unlike the gate. In this paper, hardware components of the camera, illumination, and sensor lamp were altered and software elements of an algorithm were changed. that is, the difference of the brightness of the surrounding environment, and etc. were regulated for recognize a container number. Through this, a shadow problem, and etc. that it is thickly below hung with the sunlight or the cargo equipment were solved and the recognition time was shortened and the recognition rate was raised.

• Journal of the Korean Society of Mineral and Energy Resources Engineers
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• v.55 no.6
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• pp.576-587
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• 2018

This study has focused on analysis factors affecting safety monitoring system at tailings sites, and the evaluation equipment to monitor the factors. Twenty sites at eighteen mines with unsafe conditions were selected to examine the equipment. There were three main factors influenced safety in the sites including surface erosion, piping, and slope instability. In detail, the surface erosion was divided into three sub-factors (planting, soil-topping layer, and tailings), piping into three sub-factors (liner, rain protection facility and leachate), and slop instability was also divided into three sub-factors (slop, concrete wall, and reinforcing wall). As results of in-field measurement, a CCTV was the most effective facility, and electrical resistivity survey, acoustic sensing, thermal liner sensor, structure inclinometer, rainfall meter, and flowmeter were also highly effective. According to applications of the facilities in the unstable tailings, structural defects were mainly found in the piping, which was the most important monitoring factor for safety management of tailings sites.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.21 no.5
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• pp.253-273
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• 2022

Automated vehicles rely on information collected through sensors to drive. Therefore, the uncertainty of the information collected from a sensor is an important to address. To this end, research is conducted in the field of road and traffic to solve the uncertainty of these sensors through infrastructure or facilities. Therefore, this study developed a traffic cone that can maintaing the gaze guidance function in the construction site by securing sufficient LiDAR detection performance even in rainy conditions and verified its improvement effect through demonstration. Two types of cones were manufactured, a cross-type and a flat-type, to increase the reflective performance compared to an existing cone. The demonstration confirms that the flat-type traffic cone has better detection performance than an existing cone, even in 50 mm/h rainfall, which affects a driver's field of vision. In addition, it was confirmed that the detection level on a clear day was maintained at the 20 mm/h rain for both cones. In the future, improvement measures should be developed so that the traffic cones, that can improve the safety of automated driving, can be applied.

• The Journal of Bigdata
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• v.8 no.1
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• pp.99-109
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• 2023

Recently, not only in Korea but also around the world, we have been experiencing constant disasters such as typhoons, wildfires, and heavy rains. The property damage caused by typhoons and heavy rain in South Korea alone has exceeded 1 trillion won. These disasters have resulted in significant loss of life and property damage, and the recovery process will also take a considerable amount of time. In addition, the government's contingency funds are insufficient for the current situation. To prevent and effectively respond to these issues, it is necessary to collect and analyze accurate data in real-time. However, delays and data loss can occur depending on the environment where the sensors are located, the status of the communication network, and the receiving servers. In this paper, we propose a two-stage hybrid situation analysis and prediction algorithm that can accurately analyze even in such communication network conditions. In the first step, data on river and stream levels are collected, filtered, and refined from diverse sensors of different types and stored in a bigdata. An AI rule-based inference algorithm is applied to analyze the crisis alert levels. If the rainfall exceeds a certain threshold, but it remains below the desired level of interest, the second step of deep learning image analysis is performed to determine the final crisis alert level.

• Korean Journal of Remote Sensing
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• v.35 no.6_1
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• pp.883-893
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• 2019

In this study, crop coefficients were calculated in two different methods and the results were evaluated. In the first method, appropriateness of GLDAS-based evapotranspiration was evaluated by comparing it with observed data of Cheongmi-cheon (CMC) Flux tower. Then, crop coefficient was calculated by dividing actual evapotranspiration with potential evapotranspiration that derived from GLDAS. In the second method, crop coefficient was determined by using MLR (Multiple Linear Regression) analysis with vegetation index (NDVI, EVI, LAI and SAVI) derived from MODIS and in-situ soil moisture data observed in CMC, In comparison of two crop coefficients over the entire period, for each crop coefficient GLDAS K_c and SM&VI K_c, shows the mean value of 0.412 and 0.378, the bias of 0.031 and -0.004, the RMSE of 0.092 and 0.069, and the Index of Agree (IOA) of 0.944 and 0.958. Overall, both methods showed similar patterns with observed evapotranspiration, but the SM&VI-based method showed better results. One step further, the statistical evaluation of GLDAS K_c and SM&VI K_c in specific period was performed according to the growth phase of the crop. The result shows that GLDAS K_c was better in the early and mid-phase of the crop growth, and SM&VI K_c was better in the latter phase. This result seems to be because of reduced accuracy of MODIS sensors due to yellow dust in spring and rain clouds in summer. If the observational accuracy of the MODIS sensor is improved in subsequent study, the accuracy of the SM&VI-based method will also be improved and this method will be applicable in determining the crop coefficient of unmeasured basin or predicting the crop coefficient of a certain area.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.64 no.4
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• pp.344-352
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• 2019

Drought stress caused by global climate change is a serious problem for rice cultivation. Increasingly frequent abnormal weather occurrences could include severe drought, which could cause water stress to rice during the seedling stage. This experiment was conducted to clarify the effects of drought during the seedling period on yield and quality of rice. Drought conditions were created in a rain shelter house facility. The drought treatment was conducted at 3, 10, and 20 days after transplanting. Soil water content was measured by a soil moisture sensor during the whole growth stage. In this study, we have chosen 3 rice cultivars which are widely cultivated in Korea: 'Haedamssal' (Early maturing), 'Samkwang' (Medium maturing), and 'Saenuri' (Mid-late maturing). The decrease in yield due to drought treatment was most severe 3 days after transplanting because of the decrease in the number of effective tillers. The decrease in grain quality due to drought treatment was also most severe 3 days after transplanting because of the increased protein content and hardness of the grains. The cultivar 'Haedamssal' was the most severely damaged by water stress, resulting in about a 30% yield loss. Drought conditions diminished the early vigorous growth period and days to heading in early-maturing cultivars. The results show that drought stress affects yield components immediately after transplanting, which is a decisive factor in reducing yield and grain quality. This study can be used as basic data to calculate damage compensation for drought damage on actual rice farms.