• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.11
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• pp.744-749
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• 2018

Informatization and visualization technology for real space is a key technology for construction of geospatial information. Three-dimensional (3D) modeling is a method of constructing geospatial information from data measured by various methods. The 3D laser scanner has been mainly used as a method for acquiring digital elevation data. On the other hand, the unmanned aerial vehicle (UAV), which has been attracting attention as a promising technology of the fourth industrial revolution, has been evaluated as a technology for obtaining fast geospatial information, and various studies are being carried out. However, there is a lack of evaluation on the quantitative work efficiency and data accuracy of the data construction technology for 3D geospatial modeling. In this study, various analyses were carried out on the characteristics, work processes, and accuracy of point cloud data acquired by a 3D laser scanner and an unmanned aerial vehicle. The 3D laser scanner and UAV were used to generate digital elevation data of the study area, and the characteristics were analyzed. Through evaluation of the accuracy, it was confirmed that digital elevation data from a 3D laser scanner and UAV show accuracy within a 10 cm maximum, and it is suggested that it can be used for spatial information construction. In the future, collecting 3D elevation data from a 3D laser scanner and UAV is expected to be utilized as an efficient geospatial information-construction method.

• Journal of the Korea Computer Graphics Society
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• v.28 no.2
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• pp.1-9
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• 2022

In this paper, we propose a vector-based augmentation technique that can generate data required for crack detection and a ConvNet(Convolutional Neural Network) technique that can learn it. Detecting cracks quickly and accurately is an important technology to prevent building collapse and fall accidents in advance. In order to solve this problem with artificial intelligence, it is essential to obtain a large amount of data, but it is difficult to obtain a large amount of crack data because the situation for obtaining an actual crack image is mostly dangerous. This problem of database construction can be alleviated with elastic distortion, which increases the amount of data by applying deformation to a specific artificial part. In this paper, the improved crack pattern results are modeled using ConvNet. Rather than elastic distortion, our method can obtain results similar to the actual crack pattern. By designing the crack data augmentation based on a vector, rather than the pixel unit used in general data augmentation, excellent results can be obtained in terms of the amount of crack change. As a result, in this paper, even though a small number of crack data were used as input, a crack database can be efficiently constructed by generating various crack directions and patterns.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2022.06a
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• pp.383-384
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• 2022

Following the development of technologies such as digital twin, IoT, and AI after the 4th industrial revolution, decision-making problems are being solved based on high-dimensional data analysis. This has recently been applied to the port logistics sector, and a number of studies on big data analysis, deep learning predictions, and simulations have been conducted on container terminals to improve port productivity. These high-dimensional data analysis techniques generally require a large number of data. However, the global port environment has changed due to the COVID-19 pandemic in 2020. It is not appropriate to apply data before the COVID-19 outbreak to the current port environment, and the data after the outbreak was not sufficiently collected to apply it to data analysis such as deep learning. Therefore, this study intends to present a port data augmentation method for data analysis as one of these problem-solving methods. To this end, we generate the container stowage situation of the yard through a generative adversarial neural network model in terms of container terminal operation, and verify similarity through statistical distribution verification between real and augmented data.

• Journal of the Korean Association of Geographic Information Studies
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• v.13 no.2
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• pp.119-132
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• 2010

In this study, 2-dimensional inundation analysis for Taehwa watershed in Ulsan metropolitan city was conducted to analyze flow behaviors, inundation depth and inundation stage, considering the building effect. Lidar having the interval of 1 m was employed to generate topographic data with 10m interval, and building data extracted from digital map was combined with the constructed topographic data for 2-dimensional inundation analysis. A few scenarios were constructed for the analysis to provide an effective and accurate inundation analysis method through analyzing the results. The disagreement based on the areas of inundation showed over 10% between the cases with and without consideration of building effect. The maximum inundation depth without considering the effects of buildings was 0.29m higher than that with considering the building effects. On the contrary, the maximum inundation stage with consideration of building effects was 0.49m higher than that without consideration of building effects.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.25 no.8
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• pp.838-848
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• 2014

We present a simulation study of an algorithm for the range and angle of arrival(AOA) estimation with an interferometric synthetic aperture radar(InSAR) altimeter using a real digital elevation model(DEM). We also illustrate a step-by-step procedure of generating raw InSAR data, as well as their range and azimuth compressed data, which is to be used for the subsequent altitude and angle estimation. The AOA is estimated using a deterministic maximum likelihood estimator(DMLE) applied to the first arrived point for each pulse in the compressed data obtained with three antennas. The range bin size and the pulse repetition interval(PRI) are much smaller than the cell size of the DEM used in this study. To make the DEM compatible to the radar parameters, we first generate a higher resolution DEM by linearly interpolating the given DEM. After a brief description of the principle of the InSAR altimeter, the algorithms for altitude and angle estimation are presented, and their performance is assessed through simulation.

• Asian Pacific Journal of Cancer Prevention
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• v.14 no.4
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• pp.2631-2635
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• 2013

Background: Despite recent valuable steps in initiating a cancer registry in Iran, data depicting prevalence, incidence, and clinical picture of pancreatic tumors in the country are exceedinglyly sparse. With the aim of filling this knowledge gap, we reviewed cases in the pathology archive of Shahid Sadoughi hospital (Yazd, Iran), between 2001 and 2011. Materials and Methods: Medical records of 177 patients are reported in the present study. In cases for which paraffin-embedded blocks were available, the specimens were evaluated by two independent pathologists blinded to the primary diagnosis. We extrapolated the frequency of malignant lesions in our study to the population of Yazd province, derived from national census data, to generate cancer incidence rates. Results: Final diagnosis of malignancy was made in 117 cases (66.1%), and the remainder (60 lesions, 33.9%) were classified as benign. Adenecarcinoma and neuroendocrine tumors were the two most common histological types of malignancy identified in 88 (75.2%) and 11 (9.4%) specimens, respectively. Crude annual incidence of pancreatic cancer was 0.55 per 100,000 person in 2001 and increased to 1.68 in 2011. Age standardized incidence rates in 2001 and 2011 were 0.75 and 2.68, respectively. A significant increasing trend in cancer incidence was observed during the 11 years of the study period (r=+0.856, p=0.009). Sex-stratified analysis, confirmed the observed trend in men (r=+0.728, p=0.034), but not women (r=+0.635, p=0.083). Conclusions: Over the past decade, incidence of pancreas malignancies has risen steadily in Yazd, Iran. Nevertheless, these figures are still substantially lower than those prevalent in developed nations.

• Journal of Korea Multimedia Society
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• v.11 no.2
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• pp.257-268
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• 2008

Multimedia recommendation systems analyze user preferences and recommend items(multimedia contents) to a user by predicting the user's preference for those items. Among various kinds of recommendation methods, collaborative filtering(CF) has been widely used and successfully applied to practical applications. However, collaborative filtering has two inherent problems: data sparseness and the cold-start problems. If there are few known preferences for a user, it is difficult to find many similar users, and therefore the performance of recommendation is degraded. This problem is more serious when a new user is first using the system. In this paper, we propose a method of generating additional feature of users and items into CF to overcome the difficulties caused by sparseness and improve the accuracy of recommendation. In our method, we first generate additional features by using the probability distribution of feature values, then recommend items by applying collaborative filtering on the modified data to include additional features. Several experimental results that show the effectiveness of the proposed method are also presented.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.40 no.1
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• pp.69-76
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• 2020

Bridges which are components of road network consume large amounts of resources such as concrete and steel materials, which have large environmental impacts during construction. This causes a great environmental burden. In order to reduce the environmental impact caused by the construction of the bridge, the environmental impact should be reviewed based on reasonable data in the early design stage. The purpose of this study is to provide basic data for LCA-based environmental impact assessment in the process of selecting bridge type in the early design stage. For this purpose, design data for four types of PSC bridges (general PSC girder, IPC girder, e-Beam, DR girder) were collected and LCA was performed to analyze the basic unit value and impact factors of environmental load. The results of the analysis showed that the environmental impact of IPC girder was the smallest, and the environmental impact of e-Beam was 133.7% higher than that of IPC girder. In addition, concrete, reinforcement, PC strand, square timber, sheath pipe, and steel plate were derived as the main factors that generate 98.5% of the overall environmental impact of PSC girder.

• Korean Journal of Plant Taxonomy
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• v.46 no.2
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• pp.129-148
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• 2016

Plant species on oceanic islands comprise nearly 25% of described vascular plants on only 5% of the Earth's land surface yet are among the most rare and endangered plants. Conservation of plant biodiversity on islands poses particular challenges because many species occur in a few and/or small populations, and their habitats on islands are often disturbed by the activity of humans or by natural processes such as landslides and volcanoes. In addition to described species, evidence is accumulating that there are likely significant numbers of "cryptic" species in oceanic archipelagos. Plant systematists, in collaboration with others in the botanical disciplines, are critical to the discovery of the subtle diversity in oceanic island floras. Molecular data will play an ever increasing role in revealing variation in island lineages. However, the input from plant systematists and other organismal biologists will continue to be important in calling attention to morphological and ecological variation in natural populations and in the discovery of "new" populations that can inform sampling for molecular analyses. Conversely, organismal biologists can provide basic information necessary for understanding the biology of the molecular variants, including diagnostic morphological characters, reproductive biology, habitat, etc. Such basic information is important when describing new species and arguing for their protection. Hybridization presents one of the most challenging problems in the conservation of insular plant diversity, with the process having the potential to decrease diversity in several ways including the merging of species into hybrid swarms or conversely hybridization may generate stable novel recombinants that merit recognition as new species. These processes are often operative in recent radiations in which intrinsic barriers to gene flow have not evolved. The knowledge and continued monitoring of plant populations in the dynamic landscapes on oceanic islands are critical to the preservation of their plant diversity.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.33 no.1
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• pp.23-30
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• 2015

A shoreline mapping is essential for describing coastal areas, estimating coastal erosions and managing coastal properties. This study has planned to map the 3D shorelines with the airborne LiDAR(Light Detection and Ranging) data and the KOMPSAT-2 imagery, acquired in Uljin, Korea. Following to the study, the DSM(Digital Surface Model) is generated firstly with the given LiDAR data, while the NDWI(Normalized Difference Water Index) imagery is generated by the given KOMPSAT-2 imagery. The classification method is employed to generate water and land clusters from the NDWI imagery, as the 2D shorelines are selected from the boundaries between the two clusters. Lastly, the 3D shorelines are constructed by adding the elevation information obtained from the DSM into the generated 2D shorelines. As a result, the constructed 3D shorelines have had 0.90m horizontal accuracy and 0.10m vertical accuracy. This statistical results could be concluded in that the generated 3D shorelines shows the relatively high accuracy on classified water and land surfaces, but relatively low accuracies on unclassified water and land surfaces.