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Adler I.,University of Leeds | Kante M.M.,University Blaise Pascal | Kwon O.-J.,91 Daehak ro | Kwon O.-J.,Hungarian Academy of Sciences
Algorithmica | Year: 2016

Linear rank-width is a linearized variation of rank-width, and it is deeply related to matroid path-width. In this paper, we show that the linear rank-width of every n-vertex distance-hereditary graph, equivalently a graph of rank-width at most 1, can be computed in time (Formula presented.), and a linear layout witnessing the linear rank-width can be computed with the same time complexity. As a corollary, we show that the path-width of every n-element matroid of branch-width at most 2 can be computed in time (Formula presented.), provided that the matroid is given by its binary representation. To establish this result, we present a characterization of the linear rank-width of distance-hereditary graphs in terms of their canonical split decompositions. This characterization is similar to the known characterization of the path-width of forests given by Ellis, Sudborough, and Turner [The vertex separation and search number of a graph. Inf. Comput., 113(1):50–79, 1994]. However, different from forests, it is non-trivial to relate substructures of the canonical split decomposition of a graph with some substructures of the given graph. We introduce a notion of ‘limbs’ of canonical split decompositions, which correspond to certain vertex-minors of the original graph, for the right characterization. © 2016 Springer Science+Business Media New York

To verify the interconnective relationship between biodegradation efficiency and microfibril structure, recalcitrant rice straw (RS) was depolymerized using water soaking-based microbiological biodegradation (WSMB). This eco-friendly biosystem, which does not predominantly generate inhibitory metabolites, could increase both the hydrolytic accessibility and fermentation efficiency of RS. In detail, when swollen RS (with Fenton cascades) was simultaneously bio-treated with Phanerochaete chrysosporium for 12 days, the biodegradability was 65.0 % of the theoretical maximum at the stationary phase. This value was significantly higher than the 30.3 % measured from untreated RS. Similarly, the WSMB platform had an effect on the yield enhancement of ethanol productivity of 32.5 %. However, uniform exposure of fibril polymers appeared to have little impact on bioconversion yields. Additionally, the proteomic pools of the WSMB system were analyzed to understand either substrate-specific or nonspecific biocascades based on the change in microcomposite materials. Remarkably, regardless of modified microfibril chains, the significant pattern of 14 major proteins (|fold| > 2) was reasonably analogous in both systems, especially for lignocellulolysis-related targets. © 2015 Springer Science+Business Media New York

Yoo B.,91 Daehak ro | Kim J.,91 Daehak ro
Journal of Marine Science and Technology (Japan) | Year: 2015

This study proposes a path planning algorithm for marine vehicles based on machine learning. The algorithm considers the dynamic characteristics of the vehicle and disturbance effects in ocean environments. The movements of marine vehicles are influenced by various physical disturbances in ocean environments, such as wind, waves, and currents. In the present study, the effects of ocean currents are the primary consideration. A kinematic model is used to incorporate the nonholonomic motion characteristics of a marine vehicle, and the reinforcement learning algorithm is used for path optimization to generate a feasible path that can be tracked by the vehicle. The proposed approach determines a near-optimal path that connects the start and goal points with a reasonable computational cost when the map and current field data are provided. To verify the optimality and validity of the proposed algorithm, a set of simulations were performed in simulated and actual ocean current conditions, and their results are presented. © 2015 JASNAOE

Kim T.,91 Daehak ro | Kim J.,91 Daehak ro | Choi H.-T.,Korea Research Institute of Ships and Ocean Engineering
Intelligent Service Robotics | Year: 2016

Mobile robots are generally equipped with proprioceptive motion sensors such as odometers and inertial sensors. These sensors are used for dead-reckoning navigation in an indoor environment where GPS is not available. However, this dead-reckoning scheme is susceptible to drift error in position and heading. This study proposes using grid line patterns which are often found on the surface of floors or ceilings in an indoor environment to obtain pose (i.e., position and orientation) fix information without additional external position information by artificial beacons or landmarks. The grid lines can provide relative pose information of a robot with respect to the grid structure and thus can be used to correct the pose estimation errors. However, grid line patterns are repetitive in nature, which leads to difficulties in estimating its configuration and structure using conventional Gaussian filtering that represent the system uncertainty using a unimodal function (e.g., Kalman filter). In this study, a probabilistic sensor model to deal with multiple hypotheses is employed and an online navigation filter is designed in the framework of particle filtering. To demonstrate the performance of the proposed approach, an experiment was performed in an indoor environment using a wheeled mobile robot, and the results are presented. © 2016 Springer-Verlag Berlin Heidelberg

Lee S.-Y.,91 Daehak ro | Jung E.-S.,91 Daehak ro
Proceedings of SPIE - The International Society for Optical Engineering | Year: 2014

We propose to use EEG signals to make user authentication for requiring high security. EEG signals were measured while the subjects saw several images in sequences. Since subjectsa EEG signals are different for known and unknown images, these EEG sequences may be used to identify each subject. Correlation analysis and classification results show the feasibility of user authentication from EEG signals. ©2014 SPIE.

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