• Journal of the Korean Institute of Intelligent Systems
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• v.15 no.4
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• pp.425-430
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• 2005

Many problems can be formulated in terms nf graphs and thus solved by graph-theoretic algorithms. This paper is concerned with finding paths between nodes over the distributed and overlapped graphs. The proposed method allows multiple agents to cooperate to find paths without merging the distributed graphs. For each graph there is a designated agent which is charged of providing path-finding service for hot graph and initiating the path-finding tasks of which path starts from the graph. The proposed method earlier on constructs an abstract graph so-called viewgraph for the distributed overlapped graphs and thus enables to extract the information about how to guide the path finding over the graphs. The viewgraph is shared by all agents which determine how to coordinate other agents for the purpose of finding paths. Each agent maintains the shortest path information among the nodes which are placed in different overlapped subgraphs of her graph. Once an agent is asked to get a path from a node on her graph to another node on another's graph, she directs other agents to provide the necessary information for finding paths.

• Journal of the Korea Society for Simulation
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• v.19 no.2
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• pp.91-98
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• 2010

Conventional path-finding has focused on finding short collision-free paths. However, as computer games become more sophisticated, it is required to take tactical information like ambush points or lines of enemy sight into account. One way to make this information have an effect on path-finding is to represent a heuristic function of a search algorithm as a weighted sum of tactics. In this paper we consider the problem of learning heuristic to optimize path-finding based on given tactical information. What is meant by learning is to produce a good weight vector for a heuristic function. Training examples for learning are given by a game level-designer and will be compared with search results in every search level to update weights. This paper proposes a learning algorithm integrated with search for tactical path-finding. The perceptron-like method for updating weights is described and a simulation tool for implementing these is presented. A level-designer can mark desired paths according to characters' properties in the heuristic learning tool and then it uses them as training examples to learn weights and shows traces of paths changing along with weight learning.

• Journal of KIISE:Software and Applications
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• v.34 no.4
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• pp.368-376
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• 2007

How to represent the search space is as important as which search algorithm to use for finding natural-looking paths for moving NPC (non-player character) in computer games. Recently, various state space representation methods which have been developed for computer games are being used while A* algorithm dominates as the preferred search algorithm. These representation methods show some drawbacks such as the size of state space is too large, there is no guarantee for optimality, the path found is not natural-looking, and the generation of nodes and links is not automatic by depending on a level designer. In this paper the requirements for natural-looking paths are introduced and to find paths satisfying these requirements, the use of the generalized visibility graphs which is the extended version of the visibility graph in Robotics is proposed.

• Journal of the Korean Institute of Intelligent Systems
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• v.14 no.4
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• pp.493-498
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• 2004

A novel approach for path planning of a polygonal robot is presented. Traditional path planners perform extensive geometric searching to find the optimal path or to prove that there is no solution. The computation required to prove that there is no solution is equivalent to exhaustive search of the motion space, which is typically very expensive. Humans seems to use a set of several different path planning strategies to analyse the situation of the obstacles in the environment, and quickly recognize whether the path-planning problem is easy to solve, hard to solve or has no solution. This human path-planning strategies have motivated the development of the presented algorithm that combines qualitative shape reasoning and exhaustive geometric searching to speed up the path planning process. It has three planning stages consisting of identification of no-solution cases based on an enclosure test, a qualitative reasoning stage, and finally a complete search algorithm in case the previous two stages cannot determine of the existence of a solution path.

• The Journal of the Acoustical Society of Korea
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• v.23 no.3
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• pp.214-220
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• 2004

A computationally efficient algorithm is presented for 3-D near-field source localization using a uniform circular away (UCA). Algebraic relations are demonstrated between the incident angles (elevation angle and azimuth angle) under the far-field assumption and the actual near-field location (range. elevation angle, and azimuth angle). Using these relations as paths to follow to the peak of the 3-D MUSIC spectrum, the proposed algorithm replaces the 3-D search required in the conventional 3-D MUSIC with a 1-D path following after a 2-D initialization. thereby reducing the computational burden.

• The Korean Journal of Applied Statistics
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• v.24 no.4
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• pp.623-631
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• 2011

A major goal of time-course microarray data analysis is the detection of groups of genes that manifest similar expression patterns over time. The corresponding numerous cluster algorithms for clustering time-course microarray data have been developed. In this study, we proposed a clustering method based on the primary pharmacokinetic parameters in the pharmacokinetics study for assessment of pharmaceutical equivalents between two drug products. A real data and a simulation data was used to demonstrate the usefulness of the proposed method.

• Journal of Digital Contents Society
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• v.6 no.1
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• pp.55-62
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• 2005

In this paper, we propose the new technique to compute the optimal route by considering the direction of distribution vehicles and the location for delivery, developing the algorithm of the shortest route to approach the location as applying the gemetic algorithm. This approach makes it possible for us to find the best route even under itineraries which include many destinations. Lively studies are currently in progress on the development of vehicle navigation software, combining PDA GPS, and electronic maps. Many web-sites are providing a varier of services which use electronic maps. Popular among these services is one that computes the optimal route between two positions that a user inputs. This service of computing the optimal route plays an important role in distribution industries such as home-delivery. For the distribution system. the construction of a vehicle regulation system enables us to calculate and manipulate the optimal route for distribution vehicles, to enhance the efficiency in making use of vehicles and labor, and to reduce costs.

• The Journal of the Korea Contents Association
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• v.19 no.12
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• pp.164-172
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• 2019

In this paper, we implement a wheeled mobile robot that accurately and autonomously finds the optimal route from the starting point to the destination point based on computer vision in a complex indoor environment. We get a number of waypoints from the starting point to get the best route to the target through deep reinforcement learning. However, in the case of autonomous driving, the majority of cases do not reach their destination accurately due to external factors such as surface curvature and foreign objects. Therefore, we propose an algorithm to deepen the waypoints and destinations included in the planned route and then correct the route through the waypoint recognition while driving to reach the planned destination. We built an autonomous wheeled mobile robot controlled by Arduino and equipped with Raspberry Pi and Pycamera and tested the planned route in the indoor environment using the proposed algorithm through real-time linkage with the server in the OSX environment.

• The KIPS Transactions:PartA
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• v.9A no.2
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• pp.171-180
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• 2002

The effective and accurate data flow problem analysis uses the dominator tree and DJ graphs. The data flow problem solving is to safely reduce the flow graph to the dominator tree. The flow graph replaces a parse tree and used to accurately reduce either reducible or irreducible flow graph to the dominator tree. In this paper, in order to utilize Tarian's path compress algorithm, the Top node finding algorithm is suggested and the existing delay reduction algorithm is improved using Path compression. The delayed reduction a1gorithm using path compression actually compresses the pathway of the dominator tree by hoisting the node while reducing to delay the DJ graph. Realty, the suggested algorithm had hoisted nodes in 22% and had compressed path in 20%. The compressed dominator tree makes it possible to analyze the effective data flow analysis and brings the improved effect for the complexity of code optimization process with the node hoisting effect of code optimization process.

• Journal of KIISE:Databases
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• v.31 no.2
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• pp.183-194
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• 2004

As XML is a do facto standard for a data exchange language, there have been several researches on efficient processing XML queries. The most important thing to consider when processing XML queries is how efficiently we can process path expressions in queries. Some previous works make results by performing a sequence of join operations on all records corresponding to labels in the path expression. Others works check the existence of paths in the query using an RDBMS's string comparison operator and make results by extracting the records corresponding to the paths. In this paper we suggested a new query planning algorithm based on path containment relationships and two join operators supporting the planning algorithm. The join operators use only the records related to the paths in a query as input data, scan them only once, and generate result data using a pipelining mechanism. By analysis and experiments, we confirmed that our techniques(a new query planning algorithm and two join operators) achieved significantly higher performance than other previous works.