• ETRI Journal
• /
• v.38 no.4
• /
• pp.714-723
• /
• 2016

Considerable attention has been given to processing graph data in recent years. An efficient method for computing the node proximity is one of the most challenging problems for many applications such as recommendation systems and social networks. Regarding large-scale, mutable datasets and user queries, top-k query processing has gained significant interest. This paper presents a novel method to find top-k answers in a node proximity search based on the well-known measure, Personalized PageRank (PPR). First, we introduce a distribution state transition graph (DSTG) to depict iterative steps for solving the PPR equation. Second, we propose a weight distribution model of a DSTG to capture the states of intermediate PPR scores and their distribution. Using a DSTG, we can selectively follow and compare multiple random paths with different lengths to find the most promising nodes. Moreover, we prove that the results of our method are equivalent to the PPR results. Comparative performance studies using two real datasets clearly show that our method is practical and accurate.

• MALSORI
• /
• no.51
• /
• pp.151-165
• /
• 2004

For educational and research purposes, a Korean speech recognition platform is designed. It is based on an object-oriented architecture and can be easily modified so that researchers can readily evaluate the performance of a recognition algorithm of interest. This platform will save development time for many who are interested in speech recognition. The platform includes the following modules: Noise reduction, end-point detection, met-frequency cepstral coefficient (MFCC) and perceptually linear prediction (PLP)-based feature extraction, hidden Markov model (HMM)-based acoustic modeling, n-gram language modeling, n-best search, and Korean language processing. The decoder of the platform can handle both lexical search trees for large vocabulary speech recognition and finite-state networks for small-to-medium vocabulary speech recognition. It performs word-dependent n-best search algorithm with a bigram language model in the first forward search stage and then extracts a word lattice and restores each lattice path with a trigram language model in the second stage.

• Journal of the Korea Safety Management & Science
• /
• v.8 no.2
• /
• pp.71-80
• /
• 2006

There are many display panels in the flight cockpit and pilots get various flight information from those displays. The ergonomic layout of the displays must be determined based upon frequency of use and sequence of use. This study investigated the visual search patterns of the six display groups(one head-up-display: HUD, two multi function displays: MFDs, one engine group: EG, one flight display group: FD and others) in a fighting aircraft. Four expert pilots conducted Imaginary flight in the physical mock-up and the eye movements were collected using eye tracking system. Data of dwell time, frequency of use, and eye movement path were collected. Pilots spent most of time on HUD(55.2%), and others (21.6%), FD(14.2%), right MFD(4.7%), EG(3.2%), and left MFD(1.1%) in descending order. Similarly HUD(42.8%) and others(30.0%) were the most frequently visited displays. These data can be used in the layout of cockpit displays and the determination of optimal visual search pattern.

• The Transactions of the Korean Institute of Electrical Engineers A
• /
• v.49 no.2
• /
• pp.70-77
• /
• 2000

This paper proposes a method of solving a unit commitment problem using tabu search (TS) which is heuristic algorithm. Ts is a local search method that starts from any initial solution and attempts to determine a better solution using memory structures. In this paper, to reduce the computation time for finding the optimal solution, changing tabu list size as intensification strategy and path relinking method as diversification strategy are proposed. To show the usefulness of the proposed method, we simulated for 10 units system and 110 units system. Numerical results show improvements in the generation costs and the computation time compared with priority list, genetic algorithm(GA), and hybrid GA.

• Journal of Families and Better Life
• /
• v.15 no.4
• /
• pp.41-54
• /
• 1997

The purpose of this study is to analyze information search according to consumer's prior knowledge and degree of importance of products. Questionnare survey method was used in this research. The sample was taken from 548 university students in Seoul from 19th of June to 26th of June in 1997. Statistical methods used in this study were Frequency, Percentage, Regression and path Analysis. The major findings are summarized as follows; 1) The level of Consumer's prior knowledge showed somewhat middle. 2) Degree of importance of products showed in order of quality, A/S extension exchange price reliance of a manufacturing company a design etc. 3) Information search for the consumer's prior knowledge and importance showed high on the whole. The more prior knowledge consumer have the better they recognize for the importance of products. Therefore consumers are more likely to search information.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.8 no.4
• /
• pp.27-35
• /
• 1998

Navigation is a method to direct a mobile robot without collision when traversing the environment. This is to reach a destination without getting lost. In this paper, global and local path planning in fixed obstacle and moving obstacle using genetic algorithm are presented. First, mobile robot searches optimal global path using genetic algorithm without falling into local minima. Then if it finds a unknown obstacle, it searches new path without crashing obstacle. Also if there is a moving obstacle, mobile robot searches new optimal path without colliding with the obstacles. Various simulation results show the proposed algorithm can search a shortest path effectively.

• Journal of KIISE:Computer Systems and Theory
• /
• v.34 no.5_6
• /
• pp.195-201
• /
• 2007

A minimum terminal path decomposition of a tree is defined as a partition of the tree into edge-disjoint terminal-to-terminal paths that minimizes the weight of the longest path. In this paper, we present an $O({\mid}V{\mid}^2$time algorithm to find a minimum terminal path decomposition of trees. The algorithm reduces the given optimization problem to the binary search using the corresponding decision problem, the problem to decide whether the cost of a minimum terminal path decomposition is at most l. This decision problem is solved by dynamic programing in a single traversal of the tree.

• Journal of the Korean Operations Research and Management Science Society
• /
• v.16 no.2
• /
• pp.86-102
• /
• 1991

The purpose of this paper is to present a branch and bound algorithm for the hierarchical transportation network design problem in 2-level directed networks. This problem is to find the least cost of hierarchical transportation networks which consist of a primary path and a secondary path. The primary path is a simple path from a prespecified orgin node to a prespecified terminal node. All nodes must be either a transsipment node on the primary path or connected to that path via secondary arcs. This problem is formulated to a 0-1 inter programming problem with assignment and illegal subtour elimination equations as constaints. We show that the subproblem relaxing subtour elimination constraints is transformed to a linear programming problem by means of the totally unimodularity. Optimal solutions of this subproblem are polynoially obtained by the assignment algorithm and complementary slackness conditions. Therefore, the optimal value of this subproblme is used as a lower bound. When an optimal solution of the subproblem has an illegal subtour, a better disjoint rule is adopted as the branching strategy for reducing the number of branched problems. The computational comparison between the least bound rule and the depth first rule for the search strategy is given.

• Journal of the Korea Institute of Military Science and Technology
• /
• v.13 no.2
• /
• pp.180-187
• /
• 2010

In this paper, a global path generation method is suggested using multiple grid maps connected with the mission type of unmanned combat vehicle(UCV). In order to carry out a mission for UCV, it is essential to find a global path which is coincident with the characteristics of the mission. This can be done by considering various combat circumstances represented as grid maps such as velocity map, threat map and communication map. Cost functions of multiple grid maps are linearly combined and normalized to them simultaneously for the path generation. The proposed method is realized using $A^*$, a well known search algorithm, and cost functions are normalized in the ratio of the traverse time which is one of critical information should be provided with the operators using the velocity map. By the experiments, it is checked found global paths match with the mission type by reflecting input data of grid maps properly and the computation time is short enough to regenerate paths in real time as combat circumstances change.

• Journal of Korea Multimedia Society
• /
• v.24 no.10
• /
• pp.1346-1357
• /
• 2021

The drone technology, which is receiving a lot of attention due to the 4th industrial revolution, requires an Unmanned Aerial Vehicles'(UAVs) flight path search algorithm for automatic operation and driver assistance. Various studies related to flight path prediction and recommendation algorithms are being actively conducted, and many studies using the A-Star algorithm are typically performed. In this paper, we propose an Optimal 3D Flight Path Recommendation System for unmanned aerial vehicles. The proposed system was implemented and simulated in Unity 3D, and by indicating the meaning of the route using three different colors, such as planned route, the recommended route, and the current route were compared each other. And obstacle response experiments were conducted to cope with bad weather. It is expected that the proposed system will provide an improved user experience compared to the existing system through accurate and real-time adaptive path prediction in a 3D mixed reality environment.