• Journal of Institute of Control, Robotics and Systems
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• v.22 no.12
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• pp.1021-1026
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• 2016

The graph-based SLAM (Simultaneous Localization and Mapping) approach has been gaining much attention in SLAM research recently thanks to its ability to provide better maps and full trajectory estimations when compared to the filtering-based SLAM approach. Even though graph-based SLAM requires batch processing causing it to be computationally heavy, recent advancements in optimization and computing power enable it to run fast enough to be used in real-time. However, data association problems still require large amount of computation when building a pose graph. For example, to find loop closures it is necessary to consider the whole history of the robot trajectory and sensor data within the confident range. As a pose graph grows, the number of candidates to be searched also grows. It makes searching the loop closures a bottleneck when solving the SLAM problem. Our approach to alleviate this bottleneck is to sample a limited number of pose nodes in which loop closures are searched. We propose a heuristic for sampling pose nodes that are most advantageous to closing loops by providing a way of ranking pose nodes in order of usefulness for closing loops.

• Proceedings of the KIEE Conference
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• 2008.04a
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• pp.77-78
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• 2008

This paper proposes a new algorithm for path planning and obstacles avoidance using the ant colony optimization algorithm and the particle swarm optimization. The proposed algorithm is a new hybrid algorithm that composes of the ant colony algorithm method and the particle swarm optimization method. At first, we produce paths of a mobile robot in the static environment. And then, we find midpoints of each path using the Maklink graph. Finally, the hybrid algorithm is adopted to get a shortest path. We prove the performance of the proposed algorithm is better than that of the path planning algorithm using the ant colony optimization only through simulation.

• Journal of applied mathematics & informatics
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• v.25 no.1_2
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• pp.217-229
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• 2007

In this paper, Genetic Algorithm (GA) is used to find the Maximum Weight Independent Set (MWIS) of a graph. First, MWIS problem is formulated as a 0-1 integer programming optimization problem with linear objective function and a single quadratic constraint. Then GA is implemented with the help of this formulation. Since GA is a heuristic search method, exact solution is not reached in every run. Though the suboptimal solution obtained is very near to the exact one. Computational result comprising an average performance is also presented here.

• Journal of information and communication convergence engineering
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• v.9 no.2
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• pp.141-149
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• 2011

We consider the problem of assigning tasks to homogeneous nodes in the distributed system, so as to minimize the amount of communication, while balancing the processors' loads. This issue can be posed as the graph partitioning problem. Given an undirected graph G=(nodes, edges), where nodes represent task modules and edges represent communication, the goal is to divide n, the number of processors, as to balance the processors' loads, while minimizing the capacity of edges cut. Since these two optimization criteria conflict each other, one has to make a compromise between them according to the given task type. We propose a new cost function to evaluate static task assignments and a heuristic algorithm to solve the transformed problem, explicitly describing the tradeoff between the two goals. Simulation results show that our approach outperforms an existing representative approach for a variety of task and processing systems.

• Journal of applied mathematics & informatics
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• v.5 no.2
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• pp.329-336
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• 1998

The class of doubly chordal graphs is a subclass of chordal graphs and a superclass of strongly chordal graphs which arise in so many application areas. Many optimization problems like domination and Steiner tree are NP-complete on chordal graps but can be solved in polynomial time on doubly chordal graphs. The central to designing efficient algorithms for doulby chordal graphs is the concept of (canonical)doubly perfect elimination orderings. We present linear time algorithms to compute a (canonical) double perfect elimination ordering of a doubly chordal graph.

• Communications for Statistical Applications and Methods
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• v.11 no.3
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• pp.609-617
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• 2004

To present graph of probability densities, many softwares and graphical tools use methods that link points or straight lines. However, the methods can't display exactly and smoothly the graph and are not efficient from the viewpoint of process time. One method to overcome these shortcomings is utilizing interpolation methods. In these methods, selecting the number and location of knots is an important factor. This article proposes an algorithm to select knots for graphically presenting densities and implements graph components based on the algorithm.

• Bulletin of the Korean Mathematical Society
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• v.56 no.3
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• pp.569-583
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• 2019

Given a graph G, the Motzkin and Straus formulation of the maximum clique problem is the quadratic program (QP) formed from the adjacent matrix of the graph G over the standard simplex. It is well-known that the global optimum value of this QP (called Lagrangian) corresponds to the clique number of a graph. It is useful in practice if similar results hold for hypergraphs. In this paper, we attempt to explore the relationship between the Lagrangian of a hypergraph and the order of its maximum cliques when the number of edges is in a certain range. Specifically, we obtain upper bounds for the Lagrangian of a hypergraph when the number of edges is in a certain range. These results further support a conjecture introduced by Y. Peng and C. Zhao (2012) and extend a result of J. Talbot (2002). We also establish an upper bound of the clique number in terms of Lagrangians for hypergraphs.

• Proceedings of the Korea Information Processing Society Conference
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• 2023.05a
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• pp.386-388
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• 2023

본 논문은 고성능 스토리지를 사용하는 환경에서 대규모 그래프를 분석을 위한 GPU 기반 그래프 분석 엔진의 I/O 최적화 전략을 제안한다. 사전 실험을 통해 최신 GPU 기반 그래프 엔진인 RealGraph^GPU 가 고성능 스토리지의 대역폭을 충분히 활용하지 못하고 있음을 발견하였다. 이를 개선하기 위해 (1) User-space I/O, (2) Asynchronous I/O 두 가지 최적화 전략을 적용하였으며, 실험을 통해 두 전략이 RealGraphGPU 의 그래프 분석 성능 향상시키는 데 효과적임을 확인하였다.

• KIISE Transactions on Computing Practices
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• v.23 no.8
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• pp.473-480
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• 2017

In recent years, semiconductor-based storage devices such as flash memory (SSDs) have been developed to high performance. In addition, a trend has been observed of optimally utilizing resources such as the central processing unit (CPU) and memory of the internal controller in the storage device according to the needs of the application. This concept is called In-Storage Processing (ISP). In a storage device equipped with the ISP function, it is possible to process part of the operation executed on the host system, thus reducing the load on the host. Moreover, since the data is processed in the storage device, the data transferred to the host are reduced. In this paper, we propose a method to optimize graph query processing by utilizing these ISP functions, and show that the optimized graph processing method improves the performance of the graph 500 benchmark by up to 20%.

• Smart Structures and Systems
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• v.14 no.5
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• pp.943-960
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• 2014

A visually servoed paired structured light system (ViSP) was recently proposed as a novel estimation method of the 6-DOF (Degree-Of-Freedom) relative displacement in civil structures. In order to apply the ViSP to massive structures, multiple ViSP modules should be installed in a cascaded manner. In this configuration, the estimation errors are propagated through the ViSP modules. In order to resolve this problem, a displacement estimation error back-propagation (DEEP) method was proposed. However, the DEEP method has some disadvantages: the displacement range of each ViSP module must be constrained and displacement errors are corrected sequentially, and thus the entire estimation errors are not considered concurrently. To address this problem, a pose-graph optimized displacement estimation (PODE) method is proposed in this paper. The PODE method is based on a graph-based optimization technique that considers entire errors at the same time. Moreover, this method does not require any constraints on the movement of the ViSP modules. Simulations and experiments are conducted to validate the performance of the proposed method. The results show that the PODE method reduces the propagation errors in comparison with a previous work.