• The Journal of Korean Institute of Communications and Information Sciences
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• v.24 no.7B
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• pp.1252-1260
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• 1999

The HFC network has a architecture of a star topology in fiber optic trunks, and tree and branch topology is used in the part of coaxial cable. It is well known that the HFC upstream channel is noisy. Ingress, common mode distortion and impulse noise exist in the upstream channel. In order to provide Quality of Service(QoS) to users with real-time data such as voice, video and interactive services, the evolving IEEE 802.14 standard for HFC networks must include an effective priority scheme. The scheme separates and resolves collisions between stations in a priority order. It is important to simulate protocols under a practical environment. The proposed algorithm in this paper is simulated with the assumption that the collision detector made certain mistake due to noises. Simulation results show that the proposed algorithm is more efficient than existing tree-based algorithm under practical environment.

• Journal of Information Processing Systems
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• v.16 no.6
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• pp.1324-1342
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• 2020

Various modified algorithms of rapidly-exploring random tree (RRT) have been previously proposed. However, compared to the RRT algorithm for collision avoidance with global and static obstacles, it is not easy to find a collision avoidance and local path re-planning algorithm for dynamic obstacles based on the RRT algorithm. In this study, we propose boundary-RRT*, a novel-algorithm that can be applied to aerial vehicles for collision avoidance and path re-planning in a three-dimensional environment. The algorithm not only bounds the configuration space, but it also includes an implicit bias for the bounded configuration space. Therefore, it can create a path with a natural curvature without defining a bias function. Furthermore, the exploring space is reduced to a half-torus by combining it with simple right-of-way rules. When defining the distance as a cost, the proposed algorithm through numerical analysis shows that the standard deviation (σ) approaches 0 as the number of samples per unit time increases and the length of epsilon ε (maximum length of an edge in the tree) decreases. This means that a stable waypoint list can be generated using the proposed algorithm. Therefore, by increasing real-time performance through simple calculation and the boundary of the configuration space, the algorithm proved to be suitable for collision avoidance of aerial vehicles and replanning of local paths.

• Journal of Information Technology Services
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• v.10 no.4
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• pp.259-268
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• 2011

A robot education system by emulation based on Web can be efficiently used for understanding concept of robot assembly practice and control mechanism of robot by control programming. It is important to predict the path of the line tracer robot which has to be decided by the robot. Shortest Path Algorithm is a well known algorithm which searches the most efficient path between the start node and the end node. There are two related typical algorithms. Dijkstra Algorithm searches the shortest path tree from a node to the rest of the other nodes. $A^*$ Algorithm searches the shortest paths among all nodes. The delay time caused by turning the direction of navigation for the line tracer robot at the crossroads can give big differences to the travel time of the robot. So we need an efficient path determine algorithm which can solve this problem. Thus, It is necessary to analyze the overhead of changing direction of robot at multi-linked node to determine the next direction for efficient routings. In this paper, we reflect the real delay time of directional changing from the real robot. A speed based Dijkstra algorithm is proposed and compared with the previous ones to analyze the performance.

• Publications of The Korean Astronomical Society
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• v.25 no.4
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• pp.177-186
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• 2010

We developed an efficient Monte-Carlo algorithm to solve dust-scattering radiative transfer problems for continuum radiation. The method calculates the scattered intensities for various anisotropic factors ($g_i$) all at once, while actual photon packets are tracked following a scattering phase function given by a single anisotropic factor ($g_0$). The algorithm was tested by applying the method to a dust cloud embedding a star at the cloud center and found to provide accurate results within the statistical fluctuation that is intrinsic in Monte-Carlo simulations. It was found that adopting $g_0$ = 0.4 - 0.5 in the algorithm is most efficient. The method would be efficient in estimating the anisotropic factor of the interstellar dust by comparing the observed data with radiative transfer models.

• The Bulletin of The Korean Astronomical Society
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• v.43 no.1
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• pp.43.1-43.1
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• 2018

Star formation in galaxies predominantly takes place in giant molecular clouds (GMCs). While it is widely believed that UV radiation feedback from young massive stars can destroy natal GMCs by exciting HII regions and driving their expansion, our understanding on how this actually occurs remains incomplete. To quantitatively assess the effect of UV radiation feedback on cloud disruption, we conduct a series of theoretical studies on the dynamics of HII regions and its role in controlling the star formation efficiency (SFE) and lifetime of GMCs in a wide range of star-forming environments. We first develop a semi-analytic model for the expansion of spherical dusty HII regions driven by the combination of gas and radiation pressures, finding that GMCs in normal disk galaxies are destroyed by gas-pressure driven expansion with SFE < 10%, while more dense and massive clouds with higher SFE are disrupted primarily by radiation pressure. Next, we turn to radiation hydrodynamic simulations of GMC dispersal to allow for self-consistent star formation as well as inhomogeneous density and velocity structures arising from supersonic turbulence. For this, we develop an efficient parallel algorithm for ray tracing method, which enables us to probe a range of cloud masses and sizes. Our parameter study shows that the net SFE, lifetime (measured in units of free-fall time), and the importance of radiation pressure (relative to photoionization) increase primarily with the initial surface density of the cloud. Unlike in the idealized spherical model, we find that the dominant mass loss mechanism is photoevaporation rather than dynamical ejection and that a significant fraction of radiation escapes through low optical-depth channels. We will discuss the astronomical.

• The Journal of Korea Robotics Society
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• v.6 no.3
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• pp.255-262
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• 2011

Many intelligent robots have to be given environmental information to perform tasks. In this paper an intelligent robot, that is, a cleaning robot used a sensor fusing method of two sensors: LRF and StarGazer, and then was able to obtain the information. Throughout wall following using laser displacement sensor, LRF, the working area is built during the robot turn one cycle around the area. After the process of wall following, a path planning which is able to execute the work effectively is established using flow network algorithm. This paper describes an algorithm for minimal turning complete coverage path planning for intelligent robots. This algorithm divides the whole working area by cellular decomposition, and then provides the path planning among the cells employing flow networks. It also provides specific path planning inside each cell guaranteeing the minimal turning of the robots. The proposed algorithm is applied to two different working areas, and verified that it is an optimal path planning method.

• Journal of KIISE:Software and Applications
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• v.36 no.10
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• pp.836-850
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• 2009

Human posture recognition has attracted tremendous attention in ubiquitous environment, performing arts and robot control so that, recently, many researchers in pattern recognition and computer vision are working to make efficient posture recognition system. However the most of existing studies is very sensitive to human variations such as the rotation or the translation of body. This is why the feature, which is extracted from the feature extraction part as the first step of general posture recognition system, is influenced by these variations. To alleviate these human variations and improve the posture recognition result, this paper presents 3D Star Skeleton and Principle Component Analysis (PCA) based feature extraction methods in the multi-view environment. The proposed system use the 8 projection maps, a kind of depth map, as an input data. And the projection maps are extracted from the visual hull generation process. Though these data, the system constructs 3D Star Skeleton and extracts the rotation invariant feature using PCA. In experimental result, we extract the feature from the 3D Star Skeleton and recognize the human posture using the feature. Finally we prove that the proposed method is robust to human variations.

• Journal of the Korea Society of Computer and Information
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• v.10 no.5 s.37
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• pp.77-86
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• 2005

In this paper, we designed a learning algorithm of LVQ that extracts classification errors and learns ones and improves classification performance. The proposed LVQ learning algorithm is the learning Networks which is use SOM to learn initial reference vectors and out-star learning algorithm to determine the class of the output neurons of LVQ. To extract pattern vectors which cause classification errors, we proposed the error-cause condition, which uses that condition and constructed the pattern vector space which consists of the input pattern vectors that cause the classification errors and learned these pattern vectors , and improved performance of the pattern classification. To prove the performance of the proposed learning algorithm, the simulation is performed by using training vectors and test vectors that are Fisher' Iris data and EMG data, and classification performance of the proposed learning method is compared with ones of the conventional LVQ, and it was a confirmation that the proposed learning method is more successful classification than the conventional classification.

• Proceedings of the IEEK Conference
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• 2000.09a
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• pp.471-474
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• 2000

In this paper, we present multisample DSP coding technique for StarCore, SC 140 DSP. The multisample programming is a pipelining technique that exploits operand reuse both coefficients and variables within kernel. A coefficient or operand is loaded once from memory and then the value may be used by multiple ALUs. It is possible to evaluate one intermediate product from each of four output sample calculations in parallel . Therefore, parallelization has been achieved by processing multiple samples in parallel rather than multiple intermediate products belonging to only one sample. The benefits of decreasing the number of memory moves per sample is to increase the algorithm perforomance. In this paper, the multisample technique has been implemented in FIR filter calculation using Motorola StarCore DSP development tool.

• Journal of KIISE:Computer Systems and Theory
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• v.29 no.1
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• pp.22-34
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• 2002

In this paper, we consider ring embeding problem in faulty (n,k) star graphs which is recently proposed as an alternative interconnection network topology, By effectively utilizing such strategies as series of dimension expansions and even distribution of faulty nodes into sub-stars in graph itself. we prove that it is possible to construct a maximal fault-free ring excluding only faulty nodes when the number of faults is no more than n-3 and $n-k{\geq}2$, and also propose an algorithm which can embed the corresponding ring in (n.k)-star graphs This results will be applied into the multicasting applications that the underlying cycle properties on the multi-computer system.