• Proceedings of the IEEK Conference
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• 2006.06a
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• pp.631-632
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• 2006

In this paper, acquiring the more desirable to adopt design SoC for the fast hierarchical motion estimation, we exploit foreground and background search algorithm (FBSA) base on the dual arithmetic processor element(DAPE). It is possible to estimate the large search area motion displacement using a half of number PE in general operation methods. And the proposed architecture of MHME improve the VLSI design hardware through the proposed FBSA structure with DAPE to remove the local memory. The proposed FBSA which use bit array processing in search area can improve structure as like multiple processor array unit(MPAU).

• Journal of the Korea Society of Computer and Information
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• v.22 no.9
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• pp.9-16
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• 2017

The course timetabling problem is a problem assigning a set of subjects to the given classrooms and different timeslots, while satisfying various hard constraints and soft constraints. This problem is defined as a constraint satisfaction optimization problem and is known as an NP-complete problem. Various methods has been proposed such as integer programming, constraint programming and local search methods to solve a variety of course timetabling problems. In this paper, we propose an iterative improvement search method to solve the problem based on constraint programming. First, an initial solution satisfying all the hard constraints is obtained by constraint programming, and then the solution is repeatedly improved using constraint programming again by adding new constraints to improve the quality of the soft constraints. Through experimental results, we confirmed that the proposed method can find far better solutions in a shorter time than the manual method.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.40 no.6
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• pp.1142-1147
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• 2015

As a method to increase the scalability and efficiency of wireless sensor networks, a scheme to construct networks hierarchically has received considerable attention among researchers. Researches on the methods to construct wireless networks hierarchically have been conducted focusing on how to select nodes such that they constitute a backbone network of wireless network. Nodes comprising the backbone network should be connected themselves and can cover other remaining nodes. A problem to find the minimum number of nodes which satisfy these conditions is known as the minimum connected dominating set (MCDS) problem. The MCDS problem is NP-hard, therefore there is no efficient algorithm which guarantee the optimal solutions for this problem at present. In this paper, we propose a novel multi-start local search algorithm to solve the MCDS problem efficiently. For the performance evaluation of the proposed method, we conduct extensive experiments and report the results.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.1
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• pp.215-236
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• 2017

Obtaining accurate location information is important in practical applications of wireless sensor networks (WSNs). The distance vector hop (DV-Hop) is a frequently-used range-free localization algorithm in WSNs, but it has low localization accuracy. Moreover, despite various improvements to DV-Hop-based localization algorithms, maintaining a balance between high localization accuracy and good stability and convergence is still a challenge. To overcome these shortcomings, we proposed an improved DV-Hop localization algorithm based on the bat algorithm (IBDV-Hop) for WSNs. The IBDV-Hop algorithm incorporates optimization methods that enhance the accuracy of the average hop distance and fitness function. We also introduce a nonlinear dynamic inertial weight strategy to extend the global search scope and increase the local search accuracy. Moreover, we develop an updated solutions strategy that avoids premature convergence by the IBDV-Hop algorithm. Both theoretical analysis and simulation results show that the IBDV-Hop algorithm achieves higher localization accuracy than the original DV-Hop algorithm and other improved algorithms. The IBDV-Hop algorithm also exhibits good stability, search capability and convergence, and it requires little additional time complexity and energy consumption.

• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.720-723
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• 1997

This paper presents a cooperative control method for multiple robots. This method is based on local sensors. The proposed method integrates all information obtained by local perception through a set of sensors and generates commands without logical conflicts in designing control logic. To control multiple robots effectively, a global control strategy is proposed. These methods are constructed by using AND/OR logic and transition firing sequences in Petri nets. To evaluate these methods, the object-searching task is introduced. This task is to search an object like a box by two robots and consists of two sub-tasks, i.e., a wall tracking task and a robot tracking task. Simulation results for the object-searching task and the wall tracking task are presented to show the effectiveness of the method.

• Journal of Agricultural Extension & Community Development
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• v.15 no.2
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• pp.367-398
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• 2008

This study analyzed the disparity between the supply and demand of information demand and information provision generated among information providers(agricultural researchers) and information adopters(farmers), the two subjects of the local innovation diffusion process, with a focus on the contents and methods of sharing information and according to individual innovation diffusion pattern. In information provision, the characteristics of the contents of information in terms of their temporal necessity and effective period were more important than the field to which the contents of information belonged. In addition, the selection and strategic provision of an information provision method appropriate to each pattern according to the contents of information were proposed as a way of resolving farmers'information demand and strengthening their links to experiment stations. According to the analysis, information provision methods such as the limited use of some patterns in methods of providing documents, provision of production information using experiment field, and eco-friendly agricultural information to all types through regular study group sessions, search for plans for using ICT, and supplementary and interconnected composition of individual information provision methods were applicable in a complex manner according to the situation and management format, and the standard here was the contents of information.

• Journal of Korea Multimedia Society
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• v.7 no.8
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• pp.1025-1034
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• 2004

This paper proposes an adaptive motion estimation algorithm using the temporal continuity of motion. We set up a squared global search region (GSR), which basically corresponds to the search region of FSA, and non-squared adaptive local search regions (LSRs), the positions for which are predicted by the motion vectors of the temporal neighbor blocks, are constructed in the GSR. The previous frame blocks that possibly have effects on the current block are to be the temporal neighbor blocks. Because motion estimation is only performed in the areas made by LSRs, we can estimate motion more correctly and reduce processing time. Experimental results show that the proposed method can enhance visual qualities with significant reductions of complexity by reducing search regions, when compared to the conventional methods.

• Transactions of the Korean Society of Automotive Engineers
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• v.6 no.4
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• pp.76-85
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• 1998

Recently, Genetic Algorithm(GA) is widely adopted into a search procedure for structural optimization, which is a stochastic direct search strategy that mimics the process of genetic evolution. This methods consist of three genetics operations maned selection, crossover and mutation. Contrast to traditional optimal design techniques which use design sensitivity analysis results, GA, being zero-order method, is very simple. So, they can be easily applicable to wide area of design optimization problems. Also, owing to multi-point search procedure, they have higher probability of converge to global optimum compared to traditional techniques which take one-point search method. In this study, a method of finding the optimum values of suspension parameters is proposed by using the GA. And vehicle is modelled as planar vehicle having 5 degree-of-freedom. The generalized coordinates are vertical motion of passenger seat, sprung mass and front and rear unsprung mass and rotate(pitch) motion of sprung mass. For rapid converge and precluding local optimum, share function which distribute chromosomes over design bound is introduced. Elitist survival model, remainder stochastic sampling without replacement method, multi-point crossover method are adopted. In the sight of the improvement of ride comfort, good result can be obtained in 5-D.O.F. vehicle model by using GA.

• Structural Engineering and Mechanics
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• v.45 no.2
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• pp.183-199
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• 2013

Current methods of analysis of trusses depend on matrix formulations based on equilibrium equations which are in fact derived from energy principles, and compatibility conditions. Recently it has been shown that the minimum energy principle, by itself, in its pure and unmodified form, can well be exploited to analyze structures when coupled with an optimization algorithm, specifically with a meta-heuristic algorithm. The resulting technique that can be called Total Potential Optimization using Meta-heuristic Algorithms (TPO/MA) has already been applied to analyses of linear and nonlinear plane trusses successfully as coupled with simulated annealing and local search algorithms. In this study the technique is applied to both 2-dimensional and 3-dimensional trusses emphasizing robustness, reliability and accuracy. The trials have shown that the technique is robust in two senses: all runs result in answers, and all answers are acceptable as to the reliability and accuracy within the prescribed limits. It has also been shown that Harmony Search presents itself as an appropriate algorithm for the purpose.

• The Journal of the Korea Contents Association
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• v.10 no.9
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• pp.107-116
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• 2010

The facility location problem is one of the traditional optimization problems. In this paper, we deal with the single source capacitated facility location problem (SSCFLP) and it is known as an NP-hard problem. Thus, it seems to be natural to use a heuristic approach such as evolutionary algorithms for solving the SSCFLP. This paper introduces a new efficient evolutionary algorithm for the SSCFLP. The proposed algorithm is devised by incorporating a general adaptive link adjustment evolutionary algorithm and three heuristic local search methods. Finally we compare the proposed algorithm with the previous algorithms and show the proposed algorithm finds optimum solutions at almost all middle size test instances and very stable solutions at larger size test instances.