Self-organized porous TiO2 and ZrO2 produced by anodization

The present work investigates the electrochemical formation of self-organized high aspect ratio TiO₂ and ZrO₂ nanotube layers. The formation and growth of a self-organized porous layer can be achieved directly by anodization without any templates in fluoride containing electrolytes. The morphology of the porous layers is affected by the electrochemical conditions such as the electrolyte composition, the pH and the exact polarization treatment (such as the potential sweep rate from the open-circuit potential to the anodizing potential). For Ti, nanotube layers are formed with diameters varying from approx. 20 nm to 100 nm and lengths from approx. 0.25 μm to 2.5 μm depending on the electrolytes and pH. On the other hand, for Zr, tubes of 50 nm in diameter and up to approx. 17 μm in length can be grown—a key parameter in this case is the potential sweep rate. The large difference between Ti and Zr in the achievable thickness of nanotube layers indicates a difference in the growth mechanism which may be based on the different chemical dissolution rates of electrochemically formed oxides.     

Randomly accessible, multilayered optical memory with a Bi(12)SiO(20) crystal

A read-and-write, randomly accessible, multilayered optical memory with a Bi(12) SiO(20) crystal as the medium is demonstrated. Data are recorded in the crystal as an absorption change that is due to the photochromic effect. These data are successfully recorded, read, and selectively erased in five layers in the crystal. The axial-separation distance between neighboring layers is 30 μm, and the lateral distance between bits is 5 μm. Selective bit erasure of the data is accomplished by illumination of the recorded bit datum with He-Ne laser light. To our knowledge, this is the first successful demonstration of the selective optical erasure of the photochromic effect in a BSO crystal.     

Three-dimensional optical bit-memory recording and reading with a photorefractive crystal: analysis and experiment

We analyze the three-dimensional refractive-index distribution that is induced locally when a laser beam is focused onto a very small region in a photorefractive crystal. The formation of the index distribution is deduced from the temporal behavior of the electron density distribution in the crystal under non-steady-state conditions. The density distribution is computed by the use of a set of the recurrence relations that was derived from Kukhtarev's equations, which describe the transport of electrons in time. In particular, we calculated the index distribution formed in Fe-doped LiNbO(3) crystals. To verify the validity of our analysis, we read, by using a phase-contrast microscope, refractive-index dots that were recorded in Fe-doped LiNbO(3) crystals. A good agreement was obtained between experimental results and the calculated phase-contrast images when the characteristics of the imaging system are taken into account. We also found that the induced index change is largest when the c axis of the LiNbO(3) crystal is oriented parallel to the polarization direction of the reading beam. Under this optimal condition, we succeeded in recording up to 10 layers of readable data in a LiNbO(3) crystal.     

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.

     

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.