New dissimilarity measure for recognizing noisy subsequence trees

Tree is a data structure used to express various objects such as semistructured data and genes. When objects are represented as trees, computing tree similarity is essential for pattern recognition and retrieval. This paper considers the noisy subsequence tree recognition problem whose purpose is to recognize the original tree, given its noisy subsequence tree. Previous research on this problem relied on constrained tree edit distance to measure the dissimilarity. However, the number of relabelings must be predetermined to compute it. This paper proposes a new dissimilarity measure for this problem. Our dissimilarity measure is obtained by counting the node edit operations included in the unit‐cost tree edit distance that contribute to the matching of node labels. The number of relabelings need not be specified to compute our dissimilarity measure. Moreover, our measure achieves more accurate recognition performance and faster execution speed than the constrained tree edit distance. Our measure is also useful to solve the tree inclusion problem which is the problem of deciding whether a tree includes another tree and shows the extent of approximate tree inclusion when a tree incompletely includes another tree. © 2011 Wiley Periodicals, Inc.     

An SNS-based model for finding collaborative partners

This paper proposes a model, Recommendation of Appropriate Partners (RAP), used on a Social Networking Service (SNS) for locating appropriate “helpers” for users based on individual users’ Chain of Friends (CoF) relationships. Using the RAP model, individual users can participate in a collaborative online community in remote locations, whereby helpers are willing to help other users solve their tasks/problems, and it is intended that both the users and helpers gain knowledge from these interactive online sessions. An example of the RAP-based system was implemented to invite Program Committee members to an international conference. The system was evaluated and the experimental results show that our model is very effective for discovering collaboration partners and finding users with similar interests in order to create communities for providing future and longer-term helping exchange.

     

Performance of SOR methods on modern vector and scalar processors

The building-cube method (BCM) is a new generation algorithm for CFD simulations. The basic idea of BCM is to simplify the algorithm in all stages of flow computation to achieve large-scale simulations. Calculation of a pressure field using the Successive Over Relaxation (SOR) method consumes most of the total execution time required for BCM. In this paper, effective implementations on modern vector and scalar processors are investigated. NEC SX-9 and Intel Nehalem-EX are the latest vector and scalar processors. Those processors have much higher peak performances than their previous-generation processors. However, their memory bandwidth improvement cannot catch up with the performance improvement of processors. This is the so-called memory wall problem. In our paper, we discuss optimization techniques for implementation of the SOR method based on architectural characteristics of these modern processors, and evaluate their effects on the sustained performances of these processors for BCM.     

Symbolic model checking for self-stabilizing algorithms

A distributed system is said to be self-stabilizing if it converges to safe states regardless of its initial state. In this paper we present our results of using symbolic model checking to verify distributed algorithms against the self-stabilizing property. In general, the most difficult problem with model checking is state explosion; it is especially serious in verifying the self-stabilizing property, since it requires the examination of all possible initial states. So far applying model checking to self-stabilizing algorithms has not been successful due to the problem of state explosion. In order to overcome this difficulty, we propose to use symbolic model checking for this purpose. Symbolic model checking is a verification method which uses Ordered Binary Decision Diagrams (OBDDs) to compactly represent state spaces. Unlike other model checking techniques, this method has the advantage that most of its computations do not depend on the initial states. We show how to verify the correctness of algorithms by means of SMV, a well-known symbolic model checker. By applying the proposed approach to several algorithms in the literature, we demonstrate empirically that the state spaces of self-stabilizing algorithms can be represented by OBDDs very efficiently. Through these case studies, we also demonstrate the usefulness of the proposed approach in detecting errors     

Inchworm robot grippers for clothes manipulation

Manipulating deformable objects like clothes, plastic, and paper by a robot is very challenging. This paper focuses on clothes manipulation as an example. A tracing manipulation method is used here to find a corner of the clothes. In this paper, tracing refers to tracing the clothes’ edge, with the robot’s movement based on feedback from sensors. One difficulty during this edge tracing is to make the robot trace smoothly and speedily without dropping the clothes in the process. This is due to the fact that deformable objects are sensitive to contact forces. A solution to this problem is to design a special robot gripper that can trace the clothes without having to worry about the clothes slipping away. In this paper, the development of inchworm-type grippers is proposed. Two sets of grippers inside a robot hand will allow the robot to trace the clothes more freely because there will always be a gripper firmly holding the clothes at any time. A unique tracing method for towel spreading using the inchworm grippers is also discussed. Experimental results have demonstrated the effectiveness of both the proposed grippers and also the algorithm. This work was presented in part at the 12th International Symposium on Artificial Life and Robotics, Oita, Japan, January 25–27, 2007     

A distributed control scheme for multiple robotic vehicles to make group formations

This paper presents a novel distributed control scheme of multiple robotic vehicles. Each robotic vehicle in this scheme has its own coordinate system, and it senses its relative position and orientation to others, in order to make group formations. Although there exists no supervisor and each robotic vehicle has only relative position feedback from the others in the local area around itself, all the robotic vehicles are stabilized, which we have succeeded in proving mathematically only in the cases where the attractions between the robots are symmetrical. Each robotic vehicle especially has a two-dimensional control input referred to as a “formation vector” and the formation is controllable by the vectors. The validity of this scheme is supported by computer simulations.     

Imitating others by composition of primitive actions: A neuro-dynamic model

This paper introduces a novel neuro-dynamical model that accounts for possible mechanisms of action imitation and learning. It is considered that imitation learning requires at least two classes of generalization. One is generalization over sensory–motor trajectory variances, and the other class is on cognitive level which concerns on more qualitative understanding of compositional actions by own and others which do not necessarily depend on exact trajectories. This paper describes a possible model dealing with these classes of generalization by focusing on the problem of action compositionality. The model was evaluated in the experiments using a small humanoid robot. The robot was trained with a set of different actions concerning object manipulations which can be decomposed into sequences of action primitives. Then the robot was asked to imitate a novel compositional action demonstrated by a human subject which are composed from prior-learned action primitives. The results showed that the novel action can be successfully imitated by decomposing and composing it with the primitives by means of organizing unified intentional representation hosted by mirror neurons even though the trajectory-level appearance is different between the ones of observed and those of self-generated.     

Tricuspid annuloplasty with Carpentier''s prosthetic ring in tricuspid insufficiency combined with mitral valve insufficiency

A case of bilateral hypernephroma treated by right heminephrectomy in situ and "benchwork" excision of two tumors from the left kidney followed by autotransplantation is presented. Follow-up examination has demonstrated good renal function with no evidence of tumor recurrence or metastasis. This case illustrates the feasibility of benchwork operation and its application to renal tumors, particularly when these tumors are bilateral and preservation of renal tissue is imperative. Long-term follow-up of patients managed by this technique is mandatory.     

Substrate effect on the temperature coefficient of resistance of La0.7Ca0.3MnO3 thin films prepared by metal organic deposition

Epitaxial La_0.7Ca_0.3MnO₃ (LCMO) thin films were successfully prepared by the metal-organic deposition process on various (001) single-crystal substrates: MgO, LaAlO₃ (LAO), SrTiO₃ (STO), and (LaAlO₃)_0.3-(SrAlTaO₆)_0.7 (LSAT). The crystallinity and the epitaxial growth of the LCMO films were characterized by X-ray diffraction (θ − 2θ scans and pole-figure analysis). The temperature dependence of the resistance of the LCMO/LSAT, LCMO/STO and LCMO/LAO films exhibit typical characteristics with a transition from the paramagnetic-insulator state to the ferromagnetic-metallic state at a temperature peak (T _p ) ranging from 258 to 270 K. However, the LCMO/MgO films exhibited a semiconducting behavior without any transition. Based on the R(T) measurement, we calculated the temperature coefficient of resistance (TCR) for a bolometric application and we obtained 22%/K, 10.2%/K and 27.5%/K for the film grown on the LSAT, STO and LAO substrates, respectively. This difference in the TCR properties is related to the strain induced by the lattice mismatch between LCMO and the different substrates.     

A distributed motion coordination strategy for multiple nonholonomic mobile robots in cooperative hunting operations

This paper presents a distributed smooth time-varying feedback control law for coordinating motions of multiple nonholonomic mobile robots of the Hilare-type to capture/enclose a target by making troop formations. This motion coordination is a cooperative behavior for security against invaders in surveillance areas. Each robot in this control law has its own coordinate system and it senses a target/invader, other robots and obstacles, to achieve this cooperative behavior without making any collision. Each robot especially has a two-dimensional control input referred to as a “formation vector” and the formation is controllable by the vectors. The validity of this control law is supported by computer simulations.