• The Bulletin of The Korean Astronomical Society
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• v.44 no.2
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• pp.68.3-68.3
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• 2019

We present the preliminary results on the formation of star clusters by cloud-cloud collision. For this purpose, we perform sub-parsec scale, radiation-hydrodynamic simulations of giant molecular clouds using a sink particle algorithm. The simulations include photo-ionization, direct radiation pressure, and non-thermal radiation pressure from infrared and Lyman alpha photons. We confirm that radiation feedback from massive stars suppresses accretion onto sink particles. We examine the collision-induced star formation and discuss the possibility on the formation of a globular cluster.

• 제어로봇시스템학회:학술대회논문집
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• 1995.10a
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• pp.110-114
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• 1995

This paper presents the on-board attitude determination algorithm for LEO (Low Earth Orbit) three-axis stabilized spacecraft. Two advanced star trackers and a three-axis Inertial Reference Unit (IRU) are assumed to be attitude sensors. The gyro in the IRU provides a direct measurement of the attitude rates. However, the attitude estimation error increases with time due to the gyro drift and noise. An update filter with measurements of star trackers and/or sun sensor is designed to update these gyro drift bias and to compensate the attitude error. Kalman Filter is adapted for the on-board update filter algorithm. Simulation results will be presented to investigate the attitude pointing performance.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.5 no.2
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• pp.344-358
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• 2011

Wireless tactical network (WTN) is the most important present-day technology enabling modern network centric warfare. It inherits many features from WMNs, since the WTN is based on existing wireless mesh networks (WMNs). However, it also has distinctive characteristics, such as hierarchical structures and tight QoS (Quality-of-Service) requirements. Little research has been conducted on hierarchical protocols to support various QoS in WMN. We require new protocols specifically optimized for WTNs. Control packets are generally required to find paths and reserve resources for QoS requirements, so data throughput is not degraded due to overhead. The fundamental solution is to adopt topology aggregation, in which a low tier node aggregates and simplifies the topology information and delivers it to a high tier node. The overhead from control packet exchange can be reduced greatly due to decreased information size. Although topology aggregation is effective for low overhead, it also causes the inaccuracy of topology information; thus, incurring low QoS support capability. Therefore, we need a new topology aggregation algorithm to achieve high accuracy. In this paper, we propose a new aggregation algorithm based on star topology. Noting the hierarchical characteristics in military and hierarchical networks, star topology aggregation can be used effectively. Our algorithm uses a limited number of bypasses to increase the exactness of the star topology aggregation. It adjusts topology parameters whenever it adds a bypass. Consequently, the result is highly accurate and has low computational complexity.

• Proceedings of the Korea Contents Association Conference
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• 2005.11a
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• pp.601-607
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• 2005

In this paper, we aggregate multi-links information between boundary nodes using the line segment scheme that aggregates topology information within PG referring bandwidth and delay parameter. To do this, we propose a modified line segment algorithm using two line segment method that represents two points which consist of delay-bandwidth pair to reduce topology information and provide a flexibility to the multiple-links aggregation. And we apply it to current star topology aggregation. Through the simulation result analysis, the proposed star topology aggregation scheme presents the better performance than existing scheme.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.16 no.3
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• pp.109-113
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• 2016

In this paper, we propose efficient LED lighting control algorithm using a David star magic square. Such algorithms increases the power reduction, the heat efficiency and LED life cycle and the efficiency of the LED lighting control consumption. Lighting system using existing Magic square algorithm could be reduced to increase the heat efficiency of the LED because the LED lighting time of the reduced cross-lighting. but it has a limit to the lighting control. If should apply the this proposed algorithm, can reduces power consumption and increases LED life-cycle, heat efficiency of LED lighting module and efficiency of the lighting control of the LED. This paper proposed that algorithm is by using a David star magic square on the LED Matrix. Divided into twelve areas to move the pattern in constant time interval, to perform the cross rotation and inversion techniques to thereby light up. In this paper proposed algorithm of this paper was compared with existing Magic square approach. As a result, power consumption and heat-value and luminous flux was reduced as the conventional lighting system. And, the LED lighting control increase the efficiency.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.31 no.5
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• pp.117-123
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• 2003

One of the most important elements in satellite attitude control is sensor technology. Generally, inertial sensors introduce drift and noise which cause continuous errors. Absolute reference is needed to eliminate the problem of the inertial sensors. Star trackers are used primarily for such a purpose. There has been relatively less research effort or ground feasibility test experience on star trackers in the domestic side despite the importance of the associated technologies. In this paper, we re-introduce the basic concept of a star tracker and present the S/W simulator for the star tracker. The star simulator may be used ground test of a star tracker for the basic functioning test or the whole spacecraft test with the star tracker assembled.

• Journal of the Society of Naval Architects of Korea
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• v.61 no.2
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• pp.106-114
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• 2024

In the 21st century, the rapid development of automation and artificial intelligence technologies is driving innovative changes in various industrial sectors. In the transportation industry, this is evident with the commercialization of autonomous vehicles. Moreover research into autonomous navigation technologies is actively underway in the aviation and maritime sectors. Consequently, for the practical implementation of autonomous ships, an effective collision avoidance algorithm has become a crucial element. Therefore, this study proposes a collision avoidance algorithm based on the Obstacle Zone by Target(OZT), which visually represents areas with a high likelihood of collisions with other ships or obstacles. The A-star algorithm was utilized to represent obstacles on a grid and assess collision risks. Subsequently, a collision avoidance algorithm was developed that performs fuzzy control based on calculated waypoints, allowing the vessel to return to its original course after avoiding the collision. Finally, the validity of the proposed algorithm was verified through collision avoidance simulations in various encounter scenarios.

• Journal of KIISE:Computer Systems and Theory
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• v.29 no.2
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• pp.65-74
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• 2002

Recently star networks are considered as attractive alternatives to the widely used hypercube for interconnection networks in parallel processing systems by many researchers. One of the fundamental communication problems on star graph networks is broadcasing In this paper we consider the broadcasting problems in star graph networks using wormhole routing. In wormhole routed system minimizing link contention is more critical for the system performance than the distance between two communicating nodes. We use Hamiltonian paths in star graph to set up link-disjoint communication paths We present a broadcast algorithm in n-dimensional star graph of N(=n!) nodes such that the total completion time is no larger than $([long_n n!]+1)$ steps where $([long_n n!]+1)$ is the lower bound This result is significant improvement over the previous n-1 step broadcasting algorithm.

• Journal of Astronomy and Space Sciences
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• v.36 no.4
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• pp.283-292
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• 2019

The purpose of this study was to develop a period analysis algorithm for detecting new variable stars in the time-series data observed by charge coupled device (CCD). We used the data from a variable star monitoring program of the CBNUO. The R filter data of some magnetic cataclysmic variables observed for more than 20 days were chosen to achieve good statistical results. World Coordinate System (WCS) Tools was used to correct the rotation of the observed images and assign the same IDs to the stars included in the analyzed areas. The developed algorithm was applied to the data of DO Dra, TT Ari, RXSJ1803, and MU Cam. In these fields, we found 13 variable stars, five of which were new variable stars not previously reported. Our period analysis algorithm were tested in the case of observation data mixed with various fields of view because the observations were carried with 2K CCD as well as 4K CCD at the CBNUO. Our results show that variable stars can be detected using our algorithm even with observational data for which the field of view has changed. Our algorithm is useful to detect new variable stars and analyze them based on existing time-series data. The developed algorithm can play an important role as a recycling technique for used data

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.2
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• pp.365-380
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• 2022

The target detection algorithm based on supervised learning is the current mainstream algorithm for target detection. A high-quality dataset is the prerequisite for the target detection algorithm to obtain good detection performance. The larger the number and quality of the dataset, the stronger the generalization ability of the model, that is, the dataset determines the upper limit of the model learning. The convolutional neural network optimizes the network parameters in a strong supervision method. The error is calculated by comparing the predicted frame with the manually labeled real frame, and then the error is passed into the network for continuous optimization. Strongly supervised learning mainly relies on a large number of images as models for continuous learning, so the number and quality of images directly affect the results of learning. This paper proposes a dataset STAR-24K (meaning a dataset for Space TArget Recognition with more than 24,000 images) for detecting common targets in space. Since there is currently no publicly available dataset for space target detection, we extracted some pictures from a series of channels such as pictures and videos released by the official websites of NASA (National Aeronautics and Space Administration) and ESA (The European Space Agency) and expanded them to 24,451 pictures. We evaluate popular object detection algorithms to build a benchmark. Our STAR-24K dataset is publicly available at https://github.com/Zzz-zcy/STAR-24K.