• Journal of Korean Society of Rural Planning
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• v.21 no.3
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• pp.171-179
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• 2015

The objectives of this research have been focussed on 1) developing prediction techniques for the flash flood and landslide based on rainfall prediction data in agricultural area and 2) developing an integrated forecasting system for the abrupt disasters using USN based real-time disaster sensing techniques. This study contains following steps to achieve the objective; 1) selecting rainfall prediction data, 2) constructing prediction techniques for flash flood and landslide, 3) developing USN and communication network protocol for detecting the abrupt disaster suitable for rural area, & 4) developing mobile application and SMS based early warning service system for local resident and tourist. Local prediction model (LDAPS, UM1.5km) supported by Korean meteorological administration was used for the rainfall prediction by considering spatial and temporal resolution. NRCS TR-20 and infinite slope stability analysis model were used to predict flash flood and landslide. There are limitations in terms of communication distance and cost using Zigbee and CDMA which have been used for existing disaster sensors. Rural suitable sensor-network module for water level and tilting gauge and gateway based on proprietary RF network were developed by consideration of low-cost, low-power, and long-distance for communication suitable for rural condition. SMS & mobile application forecasting & alarming system for local resident and tourist was set up for minimizing damage on the critical regions for abrupt disaster. The developed H/W & S/W for integrated abrupt disaster forecasting & alarming system was verified by field application.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.34 no.6
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• pp.619-627
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• 2016

Cells of a PV (photovoltaic) module can suffer defects due to various causes resulting in a loss of power output. As a malfunctioning cell has a higher temperature than adjacent normal cells, it can be easily detected with a thermal infrared sensor. A conventional method of PV cell inspection is to use a hand-held infrared sensor for visual inspection. The main disadvantages of this method, when applied to a large-scale PV power plant, are that it is time-consuming and costly. This paper presents an algorithm for automatically detecting defective PV panels using images captured with a thermal imaging camera from an UAV (unmanned aerial vehicle). The proposed algorithm uses statistical analysis of thermal intensity (surface temperature) characteristics of each PV module to verify the mean intensity and standard deviation of each panel as parameters for fault diagnosis. One of the characteristics of thermal infrared imaging is that the larger the distance between sensor and target, the lower the measured temperature of the object. Consequently, a global detection rule using the mean intensity of all panels in the fault detection algorithm is not applicable. Therefore, a local detection rule was applied to automatically detect defective panels using the mean intensity and standard deviation range of each panel by array. The performance of the proposed algorithm was tested on three sample images; this verified a detection accuracy of defective panels of 97% or higher. In addition, as the proposed algorithm can adjust the range of threshold values for judging malfunction at the array level, the local detection rule is considered better suited for highly sensitive fault detection compared to a global detection rule. In this study, we used a panel area extraction method that we previously developed; fault detection accuracy would be improved if panel area extraction from images was more precise. Furthermore, the proposed algorithm contributes to the development of a maintenance and repair system for large-scale PV power plants, in combination with a geo-referencing algorithm for accurate determination of panel locations using sensor-based orientation parameters and photogrammetry from ground control points.

• Journal of Korean Society for Geospatial Information Science
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• v.18 no.2
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• pp.29-33
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• 2010

The purpose of LiDAR ground classification is to archive both goals which are acquiring confident ground points with high precision and describing ground shape in detail. In spite of many studies about developing optimized algorithms to kick out this, it is very difficult to classify ground points and describing ground shape by airborne LiDAR data. Especially it is more difficult in a dense forested area like Korea. Principle misclassification was mainly caused by complex forest canopy hierarchy in Korea and relatively coarse LiDAR points density for ground classification. Unfortunately, a lot of LiDAR surveying performed in summer in South Korea. And by that reason, schematic LiDAR points distribution is very different from those of Europe. So, this study propose enhanced ground classification method considering Korean land cover characteristics. Firstly, this study designate highly confident candidated LiDAR points as a first ground points which is acquired by using big roller classification algorithm. Secondly, this study applied weighted gradient kernel(WGK) algorithm to find and include highly expected ground points from the remained candidate points. This study methods is very useful for reconstruct deformed terrain due to misclassification results by detecting and include important terrain model key points for describing ground shape at site. Especially in the case of deformed bank side of river area, this study showed highly enhanced classification and reconstruction results by using WGK algorithm.

• Investigative Magnetic Resonance Imaging
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• v.22 no.2
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• pp.94-101
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• 2018

Purpose: To determine the value of the appearance of the high signal intensity halo sign for detecting carotid intraplaque hemorrhage (IPH) on maximum intensity projection (MIP) of time-of-flight (TOF) MR angiography (MRA), based on high signal intensity on magnetization-prepared rapid acquisition with gradient-echo (MPRAGE) sequencing. Materials and Methods: A total of 78 carotid arteries in 65 patients with magnetization-prepared rapid acquisition gradient-echo (MPRAGE) positive on carotid plaque MR imaging were included in this study. High-resolution MR imaging was performed on a 3.0-T scanner prior to carotid endarterectomy or carotid artery stenting. Fast spin-echo T1- and T2-weighted axial imaging, TOF, and MPRAGE sequences were obtained. Carotid plaques with high signal intensity on MPRAGE > 200% that of adjacent muscle on at least two consecutive slices were defined as showing IPH. Halo sign of high signal intensity around the carotid artery was found on MIP from TOF MRA. Continuous and categorical variables were compared among groups using the Mann-Whitney test and Fisher's exact tests. Results: Of these 78 carotid arteries, 53 appeared as a halo sign on the TOF MRA. The total IPH volume of patients with a positive halo sign was significantly higher than that of patients without a halo sign ($75.0{\pm}86.8$ vs. $16.3{\pm}18.2$, P = 0.001). The maximum IPH axial wall area in patients with a positive halo sign was significantly higher than that of patients without a halo sign ($11.3{\pm}9.9$ vs. $3.7{\pm}3.6$, P = 0.000). Conclusion: High signal intensity halo of IPH on MIP of TOF MRA is associated with total volume and maximal axial wall area of IPH.

• The KIPS Transactions:PartB
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• v.15B no.3
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• pp.197-204
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• 2008

It is well known that the tracking a certain person is a vary needed technic in the humanoid robot. In robot technic, we should consider three aspects that is cloth color matching, face recognition and motion analysis. Because a robot technic use some sensors, it is many different with the robot technic to track a certain person through the CCTV images. A system speed should be fast in CCTV images, hence we must have small calculation numbers. We need the statistical variable for color matching and we adapt the eigen-face for face recognition to speed up the system. In this situation, motion analysis have to added for the propose of the efficient detecting system. But, in many motion analysis systems, the speed and the recognition rate is low because the system operates on the all image area. In this paper, we use the moving energy only on the face area which is searched when the face recognition is processed, since the moving energy has low calculation numbers. When the proposed algorithm has been compared with Girondel, V. et al's method for experiment, we obtained same recognition rate as Girondel, V., the speed of the proposed algorithm was the more faster. When the LDA has been used, the speed was same and the recognition rate was better than Girondel, V.'s method, consequently the proposed algorithm is more efficient for tracking a certain person.

• Korean Journal of Heritage: History & Science
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• v.42 no.4
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• pp.50-73
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• 2009

Recently old stone walls were designated as registered cultural properties that meant an extension of categories about cultural properties from a spot area to whole area. Moreover given the changing situation of residential pattern, which is due to rapid social change, this designation can be seen as a significant measure to keep as intact as possible traditional landscapes in agricultural and fishing villages. In this paper, I analyze the symbol system and meaning of old stone walls and attempt to pick out the cultural elements which are related to them. These days we have made efforts to various aspects for which make traditional cultural resources into cultural contents. But many studies had done before emphasized aspects for beauty only. Especially existing studies about an old stone wall was mainly focused on architectural interpretation and tourist route. So we need to build a plot around oral research and need a creative approach for sharing with tourists. Cultural contents combine the original form, potential and capabilities with media by detecting original form of culture and finding out the worth and meaning. In this paper examined the probability of using by investigating a stone wall in Sang-hak Village that is related with recovering of places to live in contemporary society and finding cultural contents. I suggest more creative ways to make cultural properties into tourist resources by considering the possibilities of place marketing using storytelling, based on an analysis of data gathered.

• Korean Journal of Agricultural and Forest Meteorology
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• v.23 no.3
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• pp.156-162
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• 2021

The number of smart farms has increased to save labor in agricultural production as the subsidy become available from central and local governments. The number of illegal greenhouses has also increased, which causes serious issues for the local governments. In the present study, we developed Mask-RCNN model to detect greenhouses based on satellite images. Greenhouses in the satellite images were labeled for training and validation of the model. The Mask-RC NN model had the average precision (AP) of 75.6%. The average precision values for 50% and 75% of overlapping area were 91.1% and 81.8%, respectively. This results indicated that the Mask-RC NN model would be useful to detect the greenhouses recently built without proper permission using a periodical screening procedure based on satellite images. Furthermore, the model can be connected with GIS to establish unified management system for greenhouses. It can also be applied to the statistical analysis of the number and total area of greenhouses.

• Journal of the Society of Disaster Information
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• v.18 no.4
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• pp.922-929
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• 2022

Purpose: The purpose of this paper is to develop a deep learning model to detect fire extinguishers in images taken from CCTVs in underground utility tunnels. Method: Various fire extinguisher images were collected for detection of fire extinguishers in the running-based underground utility tunnel, and a model applying the One-stage Detector method was developed based on the CNN algorithm. Result: The detection rate of fire extinguishers photographed within 10m through CCTV video in the underground common area is over 96%, showing excellent detection rate. However, it was confirmed that the fire extinguisher object detection rate drops sharply at a distance of 10m or more, in a state where it is difficult to see with the naked eye. Conclusion: This paper develops a model for detecting fire extinguisher objects in underground common areas, and the model shows high performance, and it is judged that it can be used for underground common area digital twin model synchronizing.

• Journal of Practical Engineering Education
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• v.16 no.3_spc
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• pp.391-399
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• 2024

All highway toll gates in Korea use low-speed WIM(Weight-In-Motion) to block overloaded cargo vehicles from entering the main highway, but some cargo vehicle owners are illegally modifying vehicles to operate variable axles and evading crackdowns by manipulating the axles. In previous studies detect all tires of a running vehicle were detected to determine whether there is axle manipulation. However, because the vehicle entry area at the highway toll gate checkpoint is very narrow, there is a problem that it is realistically difficult to film all tires of the entering vehicle in one video frame. In this paper, we proposed a system that can determine whether the axle is being operated through changes in the height of the vehicle's cargo box rather than by detecting tires. To detect changes in the height of a cargo box, we propose a method to extract the representative line of the cargo box using Hough transform and then measure the change in height of the representative line to detect the change in height of the cargo box. In addition, we propose a method to detect changes in the vertical height of a cargo box by accumulating motion vectors of pixels within a certain area of the image using optical flow. And the two methods were compared and their advantages and disadvantages were analyzed and presented.

• Journal of Chest Surgery
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• v.42 no.1
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• pp.79-86
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• 2009

Background: Background: Computed tomography (CT) is the main tool for detecting abnormalities of the thoracic aorta, but conventional CT only shows the cross-sectional images. These CT images have some limitations fo accuratly measuring the thoracic aortic diameters at various levels. Multidetector computed tomography (MDCT) overcomes these limitations. We measured the thoracic aortic diameter perpendicular to the loop-shaped thoracic aortic course and this was studied in relation to age, gender, height, weight, the body surface area, the body mass index and the presence of hypertension. Material and Method: Thirty hundred thirty one patients (males: 141 patients and females: 190 patients) who had no abnormalities of the thoracic aorta were investigated using MDCT aortography. They were divided into three age categories: 20~39 years old, 40~59 years old and over age 60. The image was reformed with multiplanar reconstruction and the diameter of the aorta was measured perpendicular to the aortic course at 5 anatomic segments. Level A was the mid-ascending aorta, level B was the distal ascending aorta, level C was the aortic arch, level D was the aortic isthmus and level E was the mid-descending aorta. Result: The mean age was 49.5 years old for males and 54.9 years old for females (p<0.05). The mean diameter of the thoracic aorta at level A was 31.1 mm, that at level B was 30.2 mm, that at level C was 26.5 mm, that at level D was 24.0 mm and that at level E was 22.6 mm. The diameters at all the levels were gradually increased with age. Hypertensive patients had larger diameters than did the non-hypertensive population. There was a positive correlation between the ascending aortic diameter (levels A&B) and height and the body surface area, but there were no statistical differences at the aortic arch (level C) and the descending aorta (levels D&E). There were no statistical differences of the weight and body mass index at all levels. Conclusion: The diameters of the thoracic aortas were directly correlated with gender, age and hypertension. Height and the body surface area were only correlated with the ascending aorta. Weight and the body mass index have no statistical difference at all levels. We measured the age related thoracic aortic diameters and the upper normal limits and we provide this data as reference values for the thoracic aortic diameter in the Korean population.