• The Transactions of the Korea Information Processing Society
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• v.6 no.9
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• pp.2311-2319
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• 1999

We present two heuristic algorithms for the task allocation problem (NP-complete problem) in parallel computing. The problem is to find an optimal mapping of multiple communicating tasks of a parallel program onto the multiple processing nodes of a distributed-memory multicomputer. The purpose of mapping these tasks into the nodes of the target architecture is the minimization of parallel execution time without sacrificing solution quality. Many heuristic approaches have been employed to obtain satisfactory mapping. Our heuristics are based on genetic algorithms and simulated annealing. We formulate an objective function as a total computational cost for a mapping configuration, and evaluate the performance of our heuristic algorithms. We compare the quality of solutions and times derived by the random, greedy, genetic, and annealing algorithms. Our experimental findings from a simulation study of the allocation algorithms are presented.

• Journal of the Korean Mathematical Society
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• v.54 no.3
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• pp.1031-1047
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• 2017

In this paper, we introduce two general iterative algorithms (one implicit algorithm and other explicit algorithm) for nonexpansive mappings in a reflexive Banach space with a uniformly $G{\hat{a}}teaux$ differentiable norm. Strong convergence theorems for the sequences generated by the proposed algorithms are established.

• Journal of KIISE:Computer Systems and Theory
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• v.33 no.8
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• pp.486-494
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• 2006

In this paper, we introduce a new solution for the load balancing problem, an important issue in parallel processing. Our heuristic load balancing technique called MGA effectively combines the benefit of both mean-field annealing (MFA) and genetic algorithms (GA). We compare the proposed MGA algorithm with other mapping algorithms (MFA, GA-l, and GA-2). A multiprocessor mapping algorithm simulation has been developed to measure performance improvement ratio of these algorithms. Our experimental results show that our new technique, the composition of heuristic mapping methods improves performance over the conventional ones, in terms of solution quality with a longer run time.

• Journal of the Korean Mathematical Society
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• v.58 no.3
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• pp.525-552
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• 2021

In this paper, we introduce two general iterative algorithms (one implicit algorithm and one explicit algorithm) for finding a common element of the solution set of the variational inequality problems for a continuous monotone mapping, the zero point set of a set-valued maximal monotone operator, and the fixed point set of a continuous pseudocontractive mapping in a Hilbert space. Then we establish strong convergence of the proposed iterative algorithms to a common point of three sets, which is a solution of a certain variational inequality. Further, we find the minimum-norm element in common set of three sets.

• Journal of the Korean Society of Industry Convergence
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• v.25 no.3
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• pp.341-347
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• 2022

This paper presents a comparison result of two simultaneous localization and mapping (SLAM) algorithms for navigation that have been proposed in literature. The performances of Extended Kalman Filter (EKF) SLAM under Gaussian condition, FastSLAM algorithms using Rao-Blackwellised method for particle filtering are compared in terms of accuracy of state estimations for localization of a robot and mapping of its environment. The algorithms were run using the same type of robot on indoor environment. The results show that the Particle filter based FastSLAM has the better performance in terms of accuracy of localization and mapping. The experimental results are discussed and compared.

• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.1708-1713
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• 1997

In teleoperation of a manipulator, kinesthetic feedback can take an essential role in the sense that it provides an operator with more realistic information. In this paper, in order to implement the concept of kinesthetic feedback, force mapping algorithms based on screw theory have been presented. In the development of such algorithms, the virtual environment has been modeled usign a spring and dampers, and the forces caused by hitting the joint limits of a conrtolled manipulator were considered. Finally, some experimental results of force mapping algorithm have been presented.

• Journal of the Korean Institute of Telematics and Electronics A
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• v.31A no.4
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• pp.106-115
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• 1994

This paper presents the design of a technology mapping system for optimizing delays of combinational and synchronous sequential logic circuits. The proposed system performs delay optimization for combinational logic circuits by remapping, buffering, and gate merging methods through the correct delay calculation in which the loading values are considered. To get time optimized synchronous sequential circuits, heuristic algorithms are proposed. The proposed algorithms reallocate registers by considering the critical path characteristics. Experimental results show that the proposed system produces a more optimized technology mapping for MCNC benchmarks compared with mis-II.

• Communications of the Korean Mathematical Society
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• v.26 no.4
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• pp.685-693
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• 2011

General framework for proximal point algorithms based on the notion of (A, ${\eta}$)-maximal monotonicity (also referred to as (A, ${\eta}$)-monotonicity in literature) is developed. Linear convergence analysis for this class of algorithms to the context of solving a general class of nonlinear variational inclusion problems is successfully achieved along with some results on the generalized resolvent corresponding to (A, ${\eta}$)-monotonicity. The obtained results generalize and unify a wide range of investigations readily available in literature.

• Journal of KIISE:Computer Systems and Theory
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• v.30 no.5_6
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• pp.213-222
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• 2003

Most existing algorithms adopt the forward mapping method that is based on vector representation. Problem of existing algorithms Is the exponential increase of memory usage with number of layers. This degrades the accuracy of the boundary pattern representation. Our method uses bitmap representation and does not require any additional post-processing for conversion of vector-form results to bitmap-form. A new and efficient algorithm is presented in this paper for the generation of hyperbolic patterns by means of backward mapping methods.

• ETRI Journal
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• v.43 no.4
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• pp.617-629
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• 2021

Although the actual visual simultaneous localization and mapping (SLAM) algorithms provide highly accurate tracking and mapping, most algorithms are too heavy to run live on embedded devices. In addition, the maps they produce are often unsuitable for path planning. To mitigate these issues, we propose a completely closed-loop online dense RGB-D SLAM algorithm targeting autonomous indoor mobile robot navigation tasks. The proposed algorithm runs live on an NVIDIA Jetson board embedded on a two-wheel differential-drive robot. It exhibits lightweight three-dimensional mapping, room-scale consistency, accurate pose tracking, and robustness to moving objects. Further, we introduce a navigation strategy based on the proposed algorithm. Experimental results demonstrate the robustness of the proposed SLAM algorithm, its computational efficiency, and its benefits for on-the-fly navigation while mapping.