Codevelopmental learning between human and humanoid robot using a dynamic neural-network model.

This paper examines characteristics of interactive learning between human tutors and a robot having a dynamic neural-network model, which is inspired by human parietal cortex functions. A humanoid robot, with a recurrent neural network that has a hierarchical structure, learns to manipulate objects. Robots learn tasks in repeated self-trials with the assistance of human interaction, which provides physical guidance until the tasks are mastered and learning is consolidated within the neural networks. Experimental results and the analyses showed the following: 1) codevelopmental shaping of task behaviors stems from interactions between the robot and a tutor; 2) dynamic structures for articulating and sequencing of behavior primitives are self-organized in the hierarchically organized network; and 3) such structures can afford both generalization and context dependency in generating skilled behaviors.     

Effect of sweep gas species on tritium release behavior from lithium titanate packed bed during 14 MeV neutron irradiation

In a fusion reactor, the prediction of tritium release behavior from breeder blanket is important to design the tritium recovery system, but the amount of tritium generated is necessary information to do that. Hence, tritium generation and recovery studies on lithium ceramics packed bed have been started by using fusion neutron source (FNS) in Japan Atomic Energy Agency (JAEA). Lithium titanate (Li₂TiO₃) was selected as tritium breeding material, and its packed bed was enclosed by the beryllium blocks, and was kept at certain temperature during fusion neutron irradiation. During irradiation, the packed bed was purged with the sweep gas continuously, and tritium released was trapped in each gas absorber selectively by chemical form. In this work, the effect of sweep gas species on tritium release behavior was investigated. In the case of sweep by helium with 1% of hydrogen, tritium in water form was released sensitively corresponding to the irradiation. This is due to existence of the water vapor in the sweep gas. On the other hand, in the case of sweep by helium without water vapor, tritium in gaseous form was released first, and release of tritium in water form was delayed from gaseous tritium and was gradually increased.     

Development of the Water Cooled Ceramic Breeder Test Blanket Module in Japan

The development of a Water Cooled Ceramic Breeder (WCCB) Test Blanket Module (TBM) is being performed as one of the most important steps toward DEMO blanket in Japan. For the TBM testing and evaluation toward DEMO blanket, the module fabrication technology development by a candidate structural material, reduced activation martensitic/ferritic steel, F82H, is one of the most critical items from the viewpoint of realization of TBM testing in ITER. In Japan, fabrication of a real scale first wall, side walls, a breeder pebble bed box and assembling of the first wall and side walls have succeeded. Recently, the real scale partial mockup of the back wall was fabricated. The fabrication procedure of the back wall, whose thickness is up to 90 mm, was confirmed toward the fabrication of the real scale back wall by F82H. Important key technologies are almost clarified for the fabrication of the real scale TBM module mockup. From the view point of testing and evaluation, development of the technology of the blanket tritium recovery, development of advanced breeder and multiplier pebbles and the development of the blanket neutronics measurement technology are also performed. Also, tritium production and recovery test using D-T neutron in the Fusion Neutronics Source (FNS) facility has been started as the verification test of tritium production performance. This paper overviews the recent achievements of the development of the WCCB TBM in Japan.     

Decomposition of timed automata for solving scheduling problems

A decomposition algorithm for scheduling problems based on timed automata (TA) model is proposed. The problem is represented as an optimal state transition problem for TA. The model comprises of the parallel composition of submodels such as jobs and resources. The procedure of the proposed methodology can be divided into two steps. The first step is to decompose the TA model into several submodels by using decomposable condition. The second step is to combine individual solution of subproblems for the decomposed submodels by the penalty function method. A feasible solution for the entire model is derived through the iterated computation of solving the subproblem for each submodel. The proposed methodology is applied to solve flowshop and jobshop scheduling problems. Computational experiments demonstrate the effectiveness of the proposed algorithm compared with a conventional TA scheduling algorithm without decomposition.     

Selectivity and stability via dendritic nonlinearity

Inspired by recent studies regarding dendritic computation, we constructed a recurrent neural network model incorporating dendritic lateral inhibition. Our model consists of an input layer and a neuron layer that includes excitatory cells and an inhibitory cell; this inhibitory cell is activated by the pooled activities of all the excitatory cells, and it in turn inhibits each dendritic branch of the excitatory cells that receive excitations from the input layer. Dendritic nonlinear operation consisting of branch-specifically rectified inhibition and saturation is described by imposing nonlinear transfer functions before summation over the branches. In this model with sufficiently strong recurrent excitation, on transiently presenting a stimulus that has a high correlation with feed- forward connections of one of the excitatory cells, the corresponding cell becomes highly active, and the activity is sustained after the stimulus is turned off, whereas all the other excitatory cells continue to have low activities. But on transiently presenting a stimulus that does not have high correlations with feedforward connections of any of the excitatory cells, all the excitatory cells continue to have low activities. Interestingly, such stimulus-selective sustained response is preserved for a wide range of stimulus intensity. We derive an analytical formulation of the model in the limit where individual excitatory cells have an infinite number of dendritic branches and prove the existence of an equilibrium point corresponding to such a balanced low-level activity state as observed in the simulations, whose stability depends solely on the signal-to-noise ratio of the stimulus. We propose this model as a model of stimulus selectivity equipped with self-sustainability and intensity-invariance simultaneously, which was difficult in the conventional competitive neural networks with a similar degree of complexity in their network architecture. We discuss the biological relevance of the model in a general framework of computational neuroscience.     

Virtual segment: Store–carry–forward relay-based support for wide-area non-real-time data exchange

We have proposed the concept of the virtual segment (VS), in which a global communication service is provided by combining a store–carry–forward scheme using vehicles with broadband wireless/wired network infrastructures along roads connected to the Internet. The VS can be a practical framework for non-real-time, asynchronous message transfer (especially for large messages) in a cost-effective manner. In this study, a critical implementation design issue, the message forward scheduling, in the VS approach is discussed and investigated through computer simulation by our developed VS simulator that has reflected the results of the field experiment for realistic performance evaluation.     

Interference of Mesoscopic Particles: Quantum–Classical Transition

We analyze the double slit interference of a mesoscopic particle. We calculate the visibility of the interference pattern in the far field case, introduce a characteristic temperature that defines the onset to decoherence and scrutinize the conditions that must be satisfied for an interference experiment to be possible.     

Correction of color information of a 3D model using a range intensity image

Most active optical range sensors record, simultaneously with the range image, the amount of light reflected at each measured surface location: this information forms what is called a range intensity image, also known as a reflectance image. This paper proposes a method that uses this type of image for the correction of the color information of a textured 3D model. This color information is usually obtained from color images acquired using a digital camera. The lighting condition for the color images are usually not controlled, thus this color information may not be accurate. On the other hand, the illumination condition for the range intensity image is known since it is obtained from a controlled lighting and observation configuration, as required for the purpose of active optical range measurement. The paper describes a method for combining the two sources of information, towards the goal of compensating for a reference range intensity image is first obtained by considering factors such as sensor properties, or distance and relative surface orientation of the measured surface. The color image of the corresponding surface portion is then corrected using this reference range intensity image. A B-spline interpolation technique is applied to reduce the noise of range intensity images. Finally, a method for the estimation of the illumination color is applied to compensate for the light source color. Experiments show the effectiveness of the correction method using range intensity images.     

Anode‐voltage‐control circuit for compensation of luminance deterioration

Abstract— An external driving circuit that has realized long lifetime, power‐consumption control, and peak luminance for organic light‐emitting diode (OLED) displays have been developed. This circuit realizes an effective method for constant‐anode‐voltage (CV) driving refered to as clamped inverter (CI) driving. The feature of CV driving is to achieve low‐power consumption compared with constant‐anode‐current (CC) driving and to control the power consumption and peak luminance according to the image because display luminance can be easily changed by controlling the anode voltage. On the other hand, CV driving has the problem that luminance deterioration appears to be serious compared with that of CC driving because the current of the OLED element decreases according to usage time. To cope with this, a lifetime compensation circuit that has increased the anode voltage so that it compensates for the luminance deterioration has been developed. This circuit can compensate not only the decrease in current but also the decrease in luminance at a constant current that CC driving cannot. However, increasing the anode voltage causes an increase in stress on the OLED element. The influence of stress on OLED lifetime was verified. As a result, it was confirmed that this circuit can extend the lifetime by 32% even if the anode voltage is increased, causing stress on the OLED structure.