• Journal of the Korea Institute of Information and Communication Engineering
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• v.13 no.11
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• pp.2367-2372
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• 2009

Recently, Many studies have been progressing to path-finding adapted dynamic information on the Terminal Based Navigation System(TBNS). The algorithms proposed are based on $A^*$ algorithm. Path-finding algorithms which use heuristic function may occur a problem of the increase of exploring cost. Path-finding with an abstract graph which expresses real road network as a simple graph is proposed for reducing dependency of heuristic and exploring cost. In this paper, two abstract graph that are different method of construction, Homogeneous Node merging($AG^H$) and Connected Node Merging($AG^C$), are implemented. In result of evaluation of performance, $AG^C$ has better performance than $AG^H$ at construction cost and the number of node access but $AG^C$ has worse performance than AGH at exploring cost.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.41 no.2
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• pp.41-50
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• 2004

Since the MPEG-4 visual standard enables content-based functionalities, it is necessary to extract video objects from video sequences. Segmentation algorithms can largely be classified into two different categories: automatic segmentation and user-assisted segmentation. In this paper, we propose a new user-assisted image segmentation method based on the active contour. If we define a shape space as a set of all possible variations from the initial curve and we assume that the shape space is linear, it can be decomposed into the column space and the left null space of the shape matrix. In the proposed method, the shape space vector in the column space describes changes from the initial curve to the imaginary feature curve, and a dynamic graph search algorithm describes the detailed shape of the object in the left null space. Since we employ the shape matrix and the SUSAN operator to outline object boundaries, the proposed algorithm can ignore unwanted feature points generated by low-level image processing operations and is, therefore, applicable to images of complex background. We can also compensate for limitations of the shape matrix with a dynamic graph search algorithm.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.3
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• pp.1336-1356
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• 2017

The spectrum scarcity crisis has resulted in a shortage of resources for many emerging wireless services, and research on dynamic spectrum management has been used to solve this problem. Game theory can allocate resources to users in an economic way through market competition. In this paper, we propose a bidding game-based spectrum allocation mechanism in cognitive radio network. In our framework, primary networks provide heterogeneous wireless service and different numbers of channels, while secondary users have diverse bandwidth demands for transmission. Considering the features of traffic and QoS demands, we design a weighted interference graph-based grouping algorithm to divide users into several groups and construct the non-interference user-set in the first step. In the second step, we propose the dynamic bidding game-based spectrum allocation strategy; we analyze both buyer's and seller's revenue and determine the best allocation strategy. We also prove that our mechanism can achieve balanced pricing schema in competition. Theoretical and simulation results show that our strategy provides a feasible solution to improve spectrum utilization, can maximize overall utility and guarantee users' individual rationality.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.1
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• pp.421-433
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• 2015

Recently, there have been fast-growing social network services based on the Internet environment and web technology development, the prevalence of smartphones, etc. Social networks also allow the users to convey the information and news so that they have a great influence on the public opinion formed by social interaction among users as well as the spread of information. On the other hand, these social networks also serve as perfect environments for rampant malware. Malware is rapidly being spread because relationships are formed on trust among the users. In this paper, an effective patch strategy is proposed to deal with malicious worms based on social networks. A graph is formed to analyze the structure of a social network, and subgroups are formed in the graph for the distributed patch strategy. The weighted directions and activities between the nodes are taken into account to select reliable key nodes from the generated subgroups, and the Incremental PageRanking algorithm reflecting dynamic social network features (addition/deletion of users and links) is used for deriving the high influential key nodes. With the patch based on the derived key nodes, the proposed method can prevent worms from spreading over social networks.

• International Journal of Naval Architecture and Ocean Engineering
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• v.11 no.1
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• pp.154-164
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• 2019

A rotor dynamic analysis is mandatory for stability and design optimization of submerged propellers and turbines. An accurate simulation requires a proper consideration of fluid-induced reaction forces. This paper presents a bi-directional coupling of a bond graph method solver and an unsteady vortex lattice method solver where the former is used to model the rotor dynamics of the power train and the latter is used to predict transient hydrodynamic forces. Due to solver coupling, determination of hydrodynamic coefficients is obsolete and added mass effects are considered automatically. Additionally, power grid and structural faults like grid fluctuations, eccentricity or failure could be investigated using the same model. In this research work a fast, time resolved dynamic simulation of the complete power train is conducted. As an example, the rotor dynamics of a tidal stream turbine is investigated under two inflow conditions: I - shear flow, II - shear flow + water waves.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.38 no.6
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• pp.608-616
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• 2001

This paper proposes a face recognition technique that effectively combines fixed graph matching (FGM) and Fisherface algorithm. EGM as one of dynamic link architecture uses not only face-shape but also the gray information of image, and Fisherface algorithm as a class specific method is robust about variations such as lighting direction and facial expression. In the proposed face recognition adopting the above two methods, linear projection per node of an image graph reduces dimensionality of labeled graph vector and provides a feature space to be used effectively for the classification. In comparison with a conventional EGM, the proposed approach could obtain satisfactory results in the perspectives of recognition speeds. Especially, we could get higher average recognition rate of 90.1% than the conventional methods by hold-out method for the experiments with the Yale Face Databases and Olivetti Research Laboratory (ORL) Databases.

• Knowledge Management Research
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• v.10 no.2
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• pp.35-48
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• 2009

The paper proposes a quantitative causal ordering map (QCOM) to combine qualitative and quantitative methods in a framework. The procedures for developing QCOM consist of three phases. The first phase is to collect partially known causal dependencies from experts and to convert them into relations and causal nodes of a model graph. The second phase is to find the global causal structure by tracing causality among relation and causal nodes and to represent it in causal ordering graph with signed coefficient. Causal ordering graph is converted into QCOM by assigning regression coefficient estimated from path analysis in the third phase. Experiments with the prediction model of Korea stock price show results as following; First, the QCOM can support the design of qualitative and quantitative model by finding the global causal structure from partially known causal dependencies. Second, the QCOM can be used as an integration tool of qualitative and quantitative model to offerhigher explanatory capability and quantitative measurability. The QCOM with static and dynamic analysis is applied to investigate the changes in factors involved in the model at present as well discrete times in the future.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.5 no.2
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• pp.108-113
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• 2005

This paper suggests a control method for an efficient topology/parameter evolution in a bond graph-based GP design framework that automatically synthesizes designs for multi-domain, lumped parameter dynamic systems. We adopt a hierarchical breeding control mechanism with fitness-level-dependent differences to obtain better balancing of topology/parameter search - biased toward topological changes at low fitness levels, and toward parameter changes at high fitness levels. As a testbed for this approach in bond graph synthesis, an eigenvalue assignment problem, which is to find bond graph models exhibiting minimal distance errors from target sets of eigenvalues, was tested and showed improved performance for various sets of eigenvalues.

• Proceedings of the Korean Society for Language and Information Conference
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• 2007.11a
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• pp.321-329
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• 2007

This paper reports on the application of network analysis approaches to investigate the characteristics of graph representations of Japanese word associations. Two semantic networks are constructed from two separate Japanese word association databases. The basic statistical features of the networks indicate that they have scale-free and small-world properties and that they exhibit hierarchical organization. A graph clustering method is also applied to the networks with the objective of generating hierarchical structures within the semantic networks. The method is shown to be an efficient tool for analyzing large-scale structures within corpora. As a utilization of the network clustering results, we briefly introduce two web-based applications: the first is a search system that highlights various possible relations between words according to association type, while the second is to present the hierarchical architecture of a semantic network. The systems realize dynamic representations of network structures based on the relationships between words and concepts.

• Journal of the Korean Institute of Telematics and Electronics
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• v.27 no.4
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• pp.571-579
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• 1990

A dynamic relocation algorithm for non-deterministic process graph in distributed computer systems is proposed. A method is represented for determining the optimal policy for processing a process tree. A general database query request is modelled by a process tree which represent a set of subprocesses together with their precedence relationship. The process allocation model is based on operating cost which is a function fo selection of site for processing operation, data reduction function and file size. By using expected values of parameters for non-deterministic process tree, the process graph and optimal policy that yield minimum operating cost are determined. As process is relocated according to threshold value and new information of parameters after the execution of low level process for non-deterministic process graph, the assigned state that approximate to optiaml solution is obtained. The proposed algorihtm is heuristic By performing algorithm for sample problems, it is shown that the proposed algorithm is good in obtaining optimal solution.