• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.7
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• pp.2568-2584
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• 2015

Spectral clustering has become one of the most popular clustering approaches in recent years. Similarity graph constructed on the data is one of the key factors that influence the performance of spectral clustering. However, the similarity graphs constructed by existing methods usually contain some unreliable edges. To construct reliable similarity graph for spectral clustering, an efficient method based on Markov random walk (MRW) is proposed in this paper. In the proposed method, theMRW model is defined on the raw k-NN graph and the neighbors of each sample are determined by the probability of the MRW. Since the high order transition probabilities carry complex relationships among data, the neighbors in the graph determined by our proposed method are more reliable than those of the existing methods. Experiments are performed on the synthetic and real-world datasets for performance evaluation and comparison. The results show that the graph obtained by our proposed method reflects the structure of the data better than those of the state-of-the-art methods and can effectively improve the performance of spectral clustering.

• Journal of the Korean Data and Information Science Society
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• v.25 no.2
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• pp.385-392
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• 2014

Random walk hypothesis is a hypothesis that explains theoretically the difficulty in forecasting in financial market. Various tests for the hypothesis have been developed so far but it is known that those tests suffer from low power and size distortion. In this article, a sign test based on slopes are suggested to overcome these difficulties. A simulation study is conducted to compare this test to the often used Dickey and Fuller (1979) test.

• The Journal of the Korea Contents Association
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• v.10 no.5
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• pp.210-219
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• 2010

Consumers differ in both horizontally and vertically. Market segmentation aims to divide horizontally different (or heterogeneous) consumers into more similar (or homogeneous) small segments. A specific consumer, however, may differ in vertically. He (or she) may belong to a different market segment from another one where he (or she) belonged to before. In consumer panel data, the vertical difference can be observed by his (or her) choice among brand alternatives are changing over time. The consumer's vertical difference has been defined as 'dynamics'. In this research, we have developed a binary probit model with random-walk coefficients to capture the consumer's dynamics. With an application to a consumer panel data, we have examined how have the random-walk coefficients changed over time.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.10 no.2
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• pp.73-82
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• 1998

In order to simulate surface discharged heat dispersion in costal area, a 2-dimensional Eulerian-Lagrangian model for far field and semi-active particle tracking random walk model in near field has been combined. The mass of discharged heat water in near field has treated as particles with buoyancy and this is eventually converted to horizontal additive dispersion in random walk equations. This model is applied to both a simplified coastal geometry and a real site. In simple application it can simulate plume-like characteristics around discharging point than a near field-model, CORMIX/3. Actual application in the Chonsu Bay shows farther spreading of heat water in near field comparing the observed data, and this shows that the developed model might be applied with satisfaction.

• Journal of the Korean Society of Combustion
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• v.8 no.3
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• pp.15-23
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• 2003

Partial quenching structure of turbulent diffusion flames in a turbulent mixing layer is investigated by the method of flame hole dynamics in order to develop a prediction model for turbulent flame lift off. The essence of flame hole dynamics is derivation of the random walk mapping, from the flame-edge theory, which governs expansion or contraction of flame holes initially created by local quenching events. The numerical simulation for flame hole dynamics is carried out in two stages. First, a direct numerical simulation is performed for constant-density fuel-air channel mixing layer to obtain the turbulent flow and mixing fields, from which a time series of two dimensional scalar dissipation rate array is extracted at a fixed virtual flame surface horizontally extending from the end of split plate to the downstream. Then, the Lagrangian simulation of the flame hole random walk mapping projected to the scalar dissipation rate array yields temporally evolving turbulent extinction process and its statistics on partial quenching characteristics. The statistical results exhibit that the chance of partial quenching is strongly influenced by the crossover scalar dissipation rate while almost unaffected by the iteration number of the mapping that can be regarded as a flame-edge speed.

• The Journal of Korea Robotics Society
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• v.9 no.1
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• pp.11-19
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• 2014

In this paper, an external torque estimation problem in one-degree-of-freedom (1-DOF) flexible-joint robot equipped with a joint-torque sensor is revisited. Since a sensor torque from the joint-torque sensor is distorted by two dynamics having a spring connection, i.e., motor dynamics and link dynamics of a flexible-joint robot, a model-based estimation, rather than a simple linear spring model, should be required to extract external torques accurately. In this paper, an external torque estimation algorithm for a 1-DOF flexible-joint robot is proposed. This algorithm estimates both an actuating motor torque from the motor dynamics and an external link torque from the link dynamics simultaneously by utilizing the flexible-joint robot model and the Kalman filter estimation based on random-walk model. The basic structure of the proposed algorithm is explained, and the performance is investigated through a custom-designed experimental testbed for a vertical situation under gravity.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.10 no.1
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• pp.37-44
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• 1998

In this study a new hybrid method is developed for solving flow-dominated transport problems accurately and effectively. The method takes the forward-tracking particle method for advection. However, differently from the random-walk Lagrangian approach it solves the diffusion process on the fixed Eulerian grids. Therefore, neither any interpolating algorithm nor a large enough number of particles is required. The method was successfully examined for both cases of instantaneous and continuous sources released at a point. Comparison with a surrounding 5-point Hermite polynomial method (Eulerian-Lagrangian method) and the random-walk pure Lagrangian method shows that the present method is superior in result accuracy and time-saving ability.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.9
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• pp.2846-2866
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• 2022

Caenorhabditis elegans exhibits sophisticated chemotaxis behavior through two parallel strategies, klinokinesis and klinotaxis, executed entirely by a small nervous circuit. It is therefore suitable for inspiring fast and energy-efficient solutions for autonomous navigation. As a random search strategy, the Lévy walk is optimal for diverse animals when foraging without external chemical cues. In this study, by combining these biological strategies for the first time, we propose a spiking neural network model for search and contour tracking of specific concentrations of environmental variables. Specifically, we first design a klinotaxis module using spiking neurons. This module works in conjunction with a klinokinesis module, allowing rapid searches for the concentration setpoint and subsequent contour tracking with small deviations. Second, we build a random exploration module. It generates a Lévy walk in the absence of concentration gradients, increasing the chance of encountering gradients. Third, considering local extrema traps, we develop a termination module combined with an escape module to initiate or terminate the escape in a timely manner. Experimental results demonstrate that the proposed model integrating these modules can switch strategies autonomously according to the information from a single sensor and control steering through output spikes, enabling the model worm to efficiently navigate across various scenarios.

• 한국전산유체공학회:학술대회논문집
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• 1995.10a
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• pp.246-252
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• 1995

The transient incompressible flow behind the bluffbody is numerically simulated using the random vortex method(RVM). Based on the vorticity formulation of the unsteady Navier-Stokes equations, the Lagrangian approach with the random walk technique is employed to account for the transport processes of the vortex elements. The random walk procedure for the diffusion process has been validated against the exact solutions. The present simulation focuses on the transition flow regime where the recirculation zone behind the bluffbody becomes highly unsteady and large-scale vortex eddies are shed from the bluffbody wake. The unsteady flow structures and the mixing characteristics behind the bluffbody are discussed in details.

• Journal of information and communication convergence engineering
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• v.11 no.3
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• pp.173-178
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• 2013

To discover objects of interest in unstructured peer-to-peer networks, the peers rely on flooding query messages which create incredible network traffic. This article evaluates the performance of an unstructured Gnutella-like protocol over mobile ad-hoc networks and proposes modifications to improve its performance. This paper offers an enhanced mechanism for an unstructured Gnutella-like network with improved peer features to better meet the mobility requirement of ad-hoc networks. The proposed system introduces a novel caching optimization technique and enhanced ultrapeer selection scheme to make communication more efficient between peers and ultrapeers. The paper also describes an enhanced query mechanism for efficient searching by applying multiple walker random walks with a jump and replication technique. According to the simulation results, the proposed system yields better performance than Gnutella, XL-Gnutella, and random walk in terms of the query success rate, query response time, network load, and overhead.