• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.26 no.4
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• pp.341-350
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• 2008

Change detection has been recognized as one of the most important steps to update city models. In this study, we thus propose a method to detect urban changes from two sets of LIDAR data acquired at different times. The main processes in the proposed method are (1) detecting change areas through subtraction between two DSMs generated from the LIDAR sets, (2) organizing the LIDAR points within the detected areas into surface patches, (3) classifying the class of each patch such as ground, vegetation, and building, and (4) determining the kinds of changes based on the properties and classes of the patches. The results which were obtained from the application of the proposed method to real data were verified as appropriate using the reference data manually acquired from the visual inspection of the orthoimages of the same area. The probability of success in change detection is assessed to 97% on an average. In conclusion, the proposed method is evaluated as a reliable, and efficient approach to change detection and thus the update of city model.

• Journal of KIISE:Software and Applications
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• v.35 no.2
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• pp.118-127
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• 2008

In this paper, we propose a method for construction of robust 3D statistical shape model in the mandible CT datasets. Our method consists of following four steps. First, we decompose a 3D input shape Into patches. Second, to generate a corresponding shape of a floating shape, all shapes in the training set are parameterized onto a disk similar to the patch topology. Third, we generate the corresponding shape by one-to-one mapping between the reference and the floating shapes. We solve the problem failed to generate the corresponding points near the patch boundary Finally, the corresponding shapes are aligned with the reference shape. Then statistical shape model is generated by principle component analysis. To evaluate the accuracy of our 3D statistical shape model of the mandible, we perform visual inspection and similarity measure using average distance difference between the floating and the corresponding shapes. In addition, we measure the compactness of statistical shape model using the modes of variation. Experimental results show that our 3D statistical shape model generated by the mandible CT datasets with various characteristics has a high similarity between the floating and corresponding shapes and is represented by the small number of modes.

• Korean journal of applied entomology
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• v.51 no.3
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• pp.235-243
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• 2012

Population dynamics of the American serpentine leafminer, Liriomyza trifolii (Burgess), were observed and modeled in order to compare the effects of air and tomato leaf temperatures inside a greenhouse using DYMEX model builder and simulator (pre-programed module based simulation programs developed by CSIRO, Australia). The DYMEX model simulator consisted of a series of modules with the parameters of temperature dependent development and oviposition models of L. trifolii were incorporated from pre-published data. Leaf surface temperatures of cherry tomato leaves (cv. 'Koko') were monitored according to three tomato plant positions (top, > 1.8 m above the ground level; middle, 0.9 - 1.2 m; bottom, 0.3 - 0.5 m) using an infrared temperature gun. Air temperature was monitored at the same three positions using a self-contained temperature logger. Data sets for the observed air temperature and average leaf surface temperatures were collected (top and bottom surfaces), and incorporated into the DYMEX simulator in order to compare the effects of air and leaf surface temperature on the population dynamics of L. trifolii. The initial population consisted of 50 eggs, which were laid by five female L. trifolii in early June. The number of L. trifolii larvae was counted by visual inspection of the tomato plants in order to verify the performance of DYMEX simulation. The egg, pupa, and adult stage of L. trifolii could not be counted due to its infeasible of visual inspection. A significant positive correlation between the observed and the predicted numbers of larvae was found when the leaf surface temperatures were incorporated into the DYMEX simulation (r = 0.97, p < 0.01), but no significant positive correlation was observed with air temperatures(r = 0.40, p = 0.18). This study demonstrated that the population dynamics of L. trifolii was affected greatly by the leaf temperatures, though to little discernible degree by the air temperatures, and thus the leaf surface temperature should be for a consideration in the management of L. trifolii within cherry tomato greenhouses.

• Journal of the Korea institute for structural maintenance and inspection
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• v.26 no.2
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• pp.28-36
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• 2022

As port structures are exposed to various extreme external loads such as wind (typhoons), sea waves, or collision with ships; it is important to evaluate the structural safety periodically. To monitor the port structure, especially the rubber fender, a fender segmentation system using a vision sensor and deep learning method has been proposed in this study. For fender segmentation, a new deep learning network that improves the encoder-decoder framework with the receptive field block convolution module inspired by the eccentric function of the human visual system into the DenseNet format has been proposed. In order to train the network, various fender images such as BP, V, cell, cylindrical, and tire-types have been collected, and the images are augmented by applying four augmentation methods such as elastic distortion, horizontal flip, color jitter, and affine transforms. The proposed algorithm has been trained and verified with the collected various types of fender images, and the performance results showed that the system precisely segmented in real time with high IoU rate (84%) and F1 score (90%) in comparison with the conventional segmentation model, VGG16 with U-net. The trained network has been applied to the real images taken at one port in Republic of Korea, and found that the fenders are segmented with high accuracy even with a small dataset.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.35 no.4
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• pp.961-968
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• 2015

As BIM has been increasingly applied to building project recently, its application to civil engineering project is also on the rise. As construction structures have been expanded and complicated in a size and type, the information for handling maintenance process has also increased. Thus, to actively utilize the BIM information created at the design stage, this study has been carried out to establish a maintenance system using a marker-less based augmented reality method, by presenting a maintenance system for the construction structures using augmented reality. A SURF algorithm is used to link the 3D objects in the design and construction phases to the maintenance phase. The presented method in this study can increase the utilization of 3D information created at the design stage, by offering an augmented reality technology at the maintenance stage. The method could also improve the efficiency of visual inspection on construction structures by augmenting 3D model of a bridge structure.

• The Bulletin of The Korean Astronomical Society
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• v.39 no.2
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• pp.50-50
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• 2014

We present a new catalog of galaxies in the wider region of the Virgo cluster, based on the Sloan Digital Sky Survey (SDSS) Data Release 7. The Extended Virgo Cluster Catalog (EVCC) covers an area of 725 deg2 or 60.1 Mpc2. It is 5.2 times larger than the footprint of the classical Virgo Cluster Catalog (VCC) and reaches out to 3.5 times the virial radius of the Virgo cluster. We selected 1324 spectroscopically targeted galaxies with radial velocities less than 3000 km s-1. In addition, 265 galaxies that have been missed in the SDSS spectroscopic survey but have available redshifts in the NASA Extragalactic Database are also included. Our selection process secured a total of 1589 galaxies of which 676 galaxies are not included in the VCC. The certain and possible cluster members are defined by means of redshift comparison with a cluster infall model. We employed two independent and complementary galaxy classification schemes: the traditional morphological classification based on the visual inspection of optical images and a characterization of galaxies from their spectroscopic features. SDSS u, g, r, i, and z passband photometry of all EVCC galaxies was performed using Source Extractor. We compare the EVCC galaxies with the VCC in terms of morphology, spatial distribution, and luminosity function. The EVCC defines a comprehensive galaxy sample covering a wider range in galaxy density that is significantly different from the inner region of the Virgo cluster. It will be the foundation for forthcoming galaxy evolution studies in the extended Virgo cluster region, complementing ongoing and planned Virgo cluster surveys at various wavelengths.

• Asian Pacific Journal of Cancer Prevention
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• v.13 no.8
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• pp.4169-4172
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• 2012

Background: The majority of women in rural India have poor or no access to cervical cancer screening services, although one.quarter of all cervical cancers in the world occur there. Several large trials have proven the efficacy of low-tech cervical cancer screening methods in the Indian context but none have documented the necessary components and processes of implementing this evidence in a low-resource setting. Methods: This paper discusses a feasible model of implementation of cervical cancer screening programme in low-resource settings developed through a pilot research project carried out in rural Tamilnadu, India. The programme used visual inspection of cervix after acetic acid application (VIA) as a screening tool, nurses in the primary care centres as the primary screeners and peer educators within Self-Help Women groups to raise community awareness. Results: The uptake of screening was initially low despite the access to a screening programme. However, the programme witnessed an incremental increase in the number of women accessing screening with increasing community awareness. Conclusions: The investigators recommend 4 key components to programme implementation in low-resource setting: 1) Evidence-based, cost-effective test and treatment available within the reach of the community; 2) Appropriate referral pathways; 3) Skilled health workers and necessary equipment; and 4) Optimisation of health literacy, beliefs, attitudes of the community.

• Asian Pacific Journal of Cancer Prevention
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• v.13 no.7
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• pp.3529-3533
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• 2012

Objectives: To investigate the current prevalence and knowledge of cervical cancer, breast cancer and reproductive tract infections (RTIs) in rural Chinese women, and to explore the acceptance and feasibility of implementing a combined screening program in rural China. Methods: A population-based, cross-sectional study was conducted among women aged 30 to 59 years old in Xiangyuan County, Shanxi Province from 2009 to 2010. Socio-demographic characteristics, knowledge of cervical cancer, breast cancer and RTIs, and the attitude toward single or combined screening were collected by an interview questionnaire. Each participant received a clinical examination of the cervix, breast and reproductive tract. Examinations included visual inspection, mammography, laboratory tests and pathological diagnosis. Results: A total of 1,530 women were enrolled in this study. The prevalence of cervical precancerous lesions, suspicious breast cancer, suspicious benign breast disease and RTIs was 1.4%, 0.2%, 14.0% and 54.3%, respectively. Cervicitis, trichomonas vaginitis, and bacterial vaginitis were the three most common RTIs among our participants. Television, radio broadcast, and public education during screening were the major source of healthcare knowledge in rural China. Moreover 99.7% of women expressed great interest in participating in a combined screening project. The affordable limit for combined screening project was only 50 RMB for more than half of the rural women. Conclusion: A combined screening program would be more effective and popular than single disease screening projects, while appropriate accompanied education and a co-pay model for its successful implementation need to be explored, especially in low-resource settings.

• The Bulletin of The Korean Astronomical Society
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• v.41 no.1
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• pp.53.2-53.2
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• 2016

We present surface photometry results of the dwarf galaxies in the nearby NGC 2784 galaxy group. We newly detected about 30 dwarf galaxy candidates at about 30 square degree area around the nearby NGC 2784 galaxy (D~10 Mpc and MV=-20.5) applying a visual inspection technique on the wide-field optical images taken by the KMTNet Supernova Program (KSP). Surface brightnesses of the objects estimated from the stacked-images with total exposure time of about 6 hours reach approximately ${\mu}V$ ~28.5 mag/arcsec2 around $3{\sigma}$ above sky background. The central surface brightness and the total absolute magnitude for the faintest candidate dwarf galaxy among about 40 galaxies including the previously known ones is ${\mu}0$, V~26.1 mag/arcsec2 and MV~-9.5 mag, respectively. The effective radii of the candidates are larger than ~200 pc. The radial number density of the dwarf galaxy candidates from the center of NGC 2784 is decreasing. The mean color (<(B-V)0>~0.7) and $S{\acute{e}}rsic$ structure parameters of the dwarfs, assuming them to be located in the NGC 2784 group, are well consistent with those of the dwarf galaxies in other groups (e.g. M83 group and the Local Group (LG)). The faint-end slope of the cumulative luminosity function (CLF) of the galaxies in NGC 2784 group is about ${\alpha}=-1.2$, which is steeper than that of the LG galaxies, but is much flatter than that of the CLF expected by a ${\Lambda}CDM$ model.

• Korean Journal of Remote Sensing
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• v.35 no.1
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• pp.117-136
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• 2019

In this study, a hybrid-type of day fog detection algorithm (DFDA) was developed based on the optical and textural characteristics of fog top, using the Himawari-8 /Advanced Himawari Imager data. Supplementary data, such as temperatures of numerical weather prediction model and sea surface temperatures of operational sea surface temperature and sea ice analysis, were used for fog detection. And 10 minutes data from visibility meter from the Korea Meteorological Administration were used for a quantitative verification of the fog detection results. Normalized albedo of fog top was utilized to distinguish between fog and other objects such as clouds, land, and oceans. The normalized local standard deviation of the fog surface and temperature difference between fog top and air temperature were also assessed to separate the fog from low cloud. Initial threshold values (ITVs) for the fog detection elements were selected using hat-shaped threshold values through frequency distribution analysis of fog cases.And the ITVs were optimized through the iteration method in terms of maximization of POD and minimization of FAR. The visual inspection and a quantitative verification using a visibility meter showed that the DFDA successfully detected a wide range of fog. The quantitative verification in both training and verification cases, the average POD (FAR) was 0.75 (0.41) and 0.74 (0.46), respectively. However, sophistication of the threshold values of the detection elements, as well as utilization of other channel data are necessary as the fog detection levels vary for different fog cases(POD: 0.65-0.87, FAR: 0.30-0.53).