• The Bulletin of The Korean Astronomical Society
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• v.37 no.2
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• pp.67-67
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• 2012

Exploring the distant universe by observing various astronomical objects and extending knowledge on the cosmos by applying human intuition and reasoning to observations are astronomers' professional activity. Astronomers are the people born under a lucky star since this elegant and beautiful job is their the only duty. Being in the 21st century we astronomers now know that galaxies are holding evolving stars and gas, and distribute in the infinite spacetime in an interesting way revealing the secrets of the beginning of the universe. Cosmic structures such as galaxies, large-scale structures, and cosmic microwave background fluctuations are also the tracers of the expansion of space and the invisible components of the energy contents of the universe. Unlike the past century we are in a situation where integral knowledge on various cosmic structures as well as that on a variety of observational and analysis tools are available to everyone and often required for our special mission. However, my experience made me think that accumulating critical questions on nature driven by curiosity is vital for researchers and far more important than absorbing knowledge from others and books. Transforming one's own question marks to acclamation marks is the reward of our life. That is THE fun.

• Journal of Computational Design and Engineering
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• v.1 no.1
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• pp.13-26
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• 2014

Recently, renovations of plant equipment have been more frequent because of the shortened lifespans of the products, and as-built models from large-scale laser-scanned data is expected to streamline rebuilding processes. However, the laser-scanned data of an existing plant has an enormous amount of points, captures intricate objects, and includes a high noise level, so the manual reconstruction of a 3D model is very time-consuming and costly. Among plant equipment, piping systems account for the greatest proportion. Therefore, the purpose of this research was to propose an algorithm which could automatically recognize a piping system from the terrestrial laser-scanned data of plant equipment. The straight portion of pipes, connecting parts, and connection relationship of the piping system can be recognized in this algorithm. Normal-based region growing and cylinder surface fitting can extract all possible locations of pipes, including straight pipes, elbows, and junctions. Tracing the axes of a piping system enables the recognition of the positions of these elements and their connection relationship. Using only point clouds, the recognition algorithm can be performed in a fully automatic way. The algorithm was applied to large-scale scanned data of an oil rig and a chemical plant. Recognition rates of about 86%, 88%, and 71% were achieved straight pipes, elbows, and junctions, respectively.

• Fire Science and Engineering
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• v.25 no.2
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• pp.88-94
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• 2011

Heat release characteristics of live fire load are an important parameter for performance oriented fire safety design of a building. While investigations have been carried out on the fire load and its burning behavior in office, residential and commercial buildings and so on, little effort has been paid for the rational treatment of fire load in bookstore. In this report, burning behavior of typical combustible objects in bookstore are studied by measuring heat release rates of bookshelf with book. Based on the results, it has reviewed fire safety when a fire accident occurs on the large bookstore and suggested peak heat release rate per burning surface, fire growth rate, etc of the live fire load required for fire safety design in bookstore.

• Journal of Broadcast Engineering
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• v.24 no.5
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• pp.765-774
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• 2019

In this paper, we propose a point cloud matching algorithm for multiple RGB-D cameras. In general, computer vision is concerned with the problem of precisely estimating camera position. Existing 3D model generation methods require a large number of cameras or expensive 3D cameras. In addition, the conventional method of obtaining the camera external parameters through the two-dimensional image has a large estimation error. In this paper, we propose a method to obtain coordinate transformation parameters with an error within a valid range by using depth image and function optimization method to generate omni-directional three-dimensional model using 8 low-cost RGB-D cameras.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.12
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• pp.4795-4815
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• 2020

Drone detection can be considered as a specific sort of small object detection, which has always been a challenge because of its small size and few features. For improving the detection rate of drones, we design a Deeper SSD network, which uses large-scale input image and deeper convolutional network to obtain more features that benefit small object classification. At the same time, in order to improve object classification performance, we implemented the up-sampling modules to increase the number of features for the low-level feature map. In addition, in order to improve object location performance, we adopted the down-sampling modules so that the context information can be used by the high-level feature map directly. Our proposed Deeper SSD and its variants are successfully applied to the self-designed drone datasets. Our experiments demonstrate the effectiveness of the Deeper SSD and its variants, which are useful to small drone's detection and recognition. These proposed methods can also detect small and large objects simultaneously.

• International Journal of Advanced Culture Technology
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• v.10 no.2
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• pp.300-306
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• 2022

Currently, Korea is building traffic infrastructure using Intelligent Transport Systems (ITS), but the pedestrian traffic accident rate is very high. The purpose of this paper is to prevent the risk of traffic accidents by jaywalking pedestrians. The development of this study aims to detect pedestrians who trespass using the public data set provided by the Artificial Intelligence Hub (AIHub). The data set uses training data: 673,150 pieces and validation data: 131,385 pieces, and the types include snow, rain, fog, etc., and there is a total of 7 types including passenger cars, small buses, large buses, trucks, large trailers, motorcycles, and pedestrians. has a class format of Learning is carried out using YOLOv5 as an implementation model, and as an object detection and edge detection method of an input image, a canny edge model is applied to classify and visualize human objects within the detected road boundary range. In this study, it was designed and implemented to detect pedestrians using the deep learning-based YOLOv5 model. As the final result, the mAP 0.5 showed a real-time detection rate of 61% and 114.9 fps at 338 epochs using the YOLOv5 model.

• Journal of architectural history
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• v.32 no.1
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• pp.7-20
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• 2023

The construction method of scaffolding structures is different from Mortise and Tenon and bucket arch structure of traditional large woodwork. It forms an independent construction system-fixing nodes with knots, a large number of diagonal braces are used to fix shelves and the structures mostly contain X-shape and triangular shape details. Simple ones include stalls, sheds, rain sheds, altars, lamp racks etc. But the scaffolding with larger scale and more complicated structure are modeled on archways, theatres and other buildings which are used in commercial and festival activities. At present, Macao, Hong Kong, Guangdong, Sichuan, Shanxi and other places in China have retained the custom of using scaffolding structures in important festival activities, but their uses, techniques and building types are slightly different from place to place. Due to building and demolishing at any time, the construction and service cycle is short. As a result, there are almost no physical objects left. We can only deduce the use and technical characteristics of ancient scaffolding skills through the colorful building styles that have been preserved with folk activities in various parts of China, the craftsmanship handed down from generation to generation by the scaffolding guild and artisans, and the description of cultural and historical materials and the mutual corroboration of visual materials.

• The Bulletin of The Korean Astronomical Society
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• v.44 no.2
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• pp.75.3-75.3
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• 2019

The filament is an interesting structure in the Universe because clusters form at the nodes of filaments and grow through the continuous accretion of individual galaxies and groups from the surrounding filaments. We study the chemical properties of star-forming (SF) galaxies in the five large-scale filamentary structures (Leo II A, Leo II B, Leo Minor, Canes Venatici, and Virgo III) related with the Virgo cluster, with the spectroscopic data taken with the SDSS DR12, and compare them with those of the Virgo cluster and field galaxies. In mass-metallicity relation, most of the SF galaxies in Virgo-related filaments (except Virgo III filament) show lower metallicity on average than the Virgo cluster SF galaxies, but similar to field counterparts. These chemically less evolved feature of SF galaxies in the filaments and field are more pronounced for lower mass galaxies. This is probably because low mass galaxies have low potential wells and are therefore likely to be sensitive to cluster environmental effects. Interestingly, we find that the metallicity enhancement of SF galaxies in the Virgo III filament. In chemical and morphological perspectives, SF galaxies in the Virgo III thought to be transitional objects possibly transformed from SF late-type galaxies and are on the way to red early-type galaxies in the filament environment. This is the first discovery of systematic 'chemical pre-processing' signature for filament galaxies in Local Universe before they fall into the cluster.

• IEMEK Journal of Embedded Systems and Applications
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• v.18 no.5
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• pp.203-208
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• 2023

Recently, with the growing interest in the field of autonomous driving, many researchers have been focusing on developing autonomous driving software platforms. In particular, we have concentrated on developing 3D object detection models that can improve real-time performance. In this paper, we introduce a self-constructed 3D LiDAR dataset specific to domestic environments and propose a VariFocal-based CenterPoint for the 3D object detection model, with improved performance over the previous models. Furthermore, we present experimental results comparing the performance of the 3D object detection modules using our self-built and public dataset. As the results show, our model, which was trained on a large amount of self-constructed dataset, successfully solves the issue of failing to detect large vehicles and small objects such as motorcycles and pedestrians, which the previous models had difficulty detecting. Consequently, the proposed model shows a performance improvement of about 1.0 mAP over the previous model.

• International Journal of CAD/CAM
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• v.4 no.1
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• pp.47-53
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• 2004

The subdivision surface is the limit of recursively refined polyhedral mesh. It is quite intuitive that the multi-resolution feature can be utilized to simplify generation of NC (Numerical Control) tool paths for rough machining. In this paper, a new method of parallel NC tool path generation for subdivision surfaces is presented. The basic idea of the method includes two steps: first, extending G-Buffer to a strip buffer (called S-Buffer) by dividing the working area into strips to generate NC tool paths for objects of large size; second, generating NC tool paths by parallel implementation of S-Buffer based on MPI (Message Passing Interface). Moreover, the recursion depth of the surface can be estimated for a user-specified error tolerance, so we substitute the polyhedral mesh for the limit surface during rough machining. Furthermore, we exploit the locality of S-Buffer and develop a dynamic division and load-balanced strategy to effectively parallelize S-Buffer.