Universality Issues in Reversible Computing Systems and Cellular Automata (Extended Abstract)

In this survey, we deal with the problem how a universal computer can be constructed in a reversible environment. We discuss this problem based on the frameworks of reversible Turing machines, reversible logic circuits, and reversible cellular automata. We can see that in spite of the constraint of reversibility, there are several very simple reversible systems that have universal computing ability.     

Development of ‘UR-System 2’: a training system for recovery of motor function of plegic upper limb after stroke

We developed a new training system, called ‘UR-System 2’, for the recovery of motor function of a plegic upper limb after stroke. UR-System 2, which was redesigned based on knowledge gained from clinical tests using UR-System 1, was newly equipped with a function for testing the motor function of patients, such as isolated movement. In order to verify the effectiveness of UR-System 2, we conducted the following procedures: we verified the safety of training in healthy persons; we gathered standard data on pronation and supination of healthy forearms during tests; and, we verified that the test function was effective in evaluating the recovery effect of isolated movement in two hemiplegic patients.     

Translational lemmas for DLOGTIME-uniform circuits,alternating TMs,and PRAMs

We present translational lemmas for the three standard models of parallel computation, and apply them to obtain tight hierarchy results. It is shown that, for arbitrarily small rational constant , (i) there is a language which can be accepted by a -uniform circuit family of depth and size but not by any -uniform circuit family of depth and size , (ii) there is a language which can be accepted by a -time -space ATM with l worktapes but not by any -time -space ATM with the same l worktapes if the number of tape symbols is fixed, and (iii) there is a language which can be accepted by a -time PRAM with processors but not by any -time PRAM with processors. Here, c > 0, d ≥ 1, r ₁ > 1, and r ₂ ≥ 1 are arbitrary rational constants, and l ≥ 2 is an arbitrary integer. Preliminary versions of different parts of this paper appeared in Proc. MCU 2004 (LNCS 3354) and Proc. FCT 2005 (LNCS 3623).     

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.     

Study of Superconducting Fault Current Limiter Using Vacuum Interrupter Driven by Electromagnetic Repulsion Force for Commutating Switch

Using a high-temperature superconductor, we constructed and tested a model superconducting fault current limiter (SFCL). The superconductor and the vacuum interrupter as the commutation switch were connected in parallel using a bypass coil. When the fault current flows in this equipment, the superconductor is quenched and the current is transferred to the parallel coil because of the voltage drop in the superconductor. This large current in the parallel coil actuates the magnetic repulsion mechanism of the vacuum interrupter. Due to the opening of the vacuum interrupter, the current in the superconductor is broken. By using this equipment, the current flow time in the superconductor can be easily minimized. On the other hand, the fault current is also easily limited by large reactance of the parallel coil     

Using selective precipitant for uranyl ions — Fundamental studies for evaluating the precipitant performance

We have developed a simple reprocessing process for spent FBR fuels using N-cyclohexyl-2-pyrrolidone (NCP) which has selective precipitation ability for UO₂²⁺ ions. It was confirmed that NCP has sufficient precipitation ability for UO₂²⁺ ions, decontamination capability (separation of UO₂²⁺ from simulated fission products), and resistance to γ-ray radiation in nitric acid solutions. These findings indicate that NCP is applicable to our reprocessing process. We have also evaluated performances of other precipitants such as N-n-propyl-2-pyrrolidone (NProP), N-n-butyl-2-pyrrolidone (NBP), and N-n-butyl-2-pyridone (NBPyr). It was found that higher decontamination factors (DFs) are obtained by using NProP and NBP. This can be interpreted that the hydrophobicity of NProP and NBP is lower than that of NCP. Furthermore, we have obtained an experimental result that the resistance of NBPyr to γ-ray radiation is superior to that of NCP.     

Analysis of the critical heat flux in round vertical tubes under low pressure and flow oscillation conditions. Applications of artificial neural network

Artificial neural networks (ANNs) for predicting critical heat flux (CHF) under low pressure and oscillation conditions have been trained successfully for either natural circulation or forced circulation (FC) in the present study. The input parameters of the ANN are pressure, mean mass flow rate, relative amplitude, inlet subcooling, oscillation period and the ratio of the heated length to the diameter of the tube, L/D. The output is a nondimensionalized factor F, which expresses the relative CHF under oscillation conditions. Based on the trained ANN, the influences of principal parameters on F for FC were analyzed. The parametric trends of the CHF under oscillation obtained by the trained ANN are as follows: the effects of pressure below 500 kPa are complex due to the influence of other parameters. F will increase with increasing mean mass flow rate under any conditions, and will decrease generally with an increase in relative amplitude. F will decrease initially and then increase with increasing inlet subcooling. The influence curves of mean mass flow rate on F will be almost the same when the period is shorter than 5.0 s or longer than 15 s. The influence of L/D will be negligible if L/D>200. It is found that the minimum number of neurons in the hidden layer is a product of the number of neurons in the input layer and in the output layer.     

A fast and compact elimination method of empty elements from a double‐array structure

A double‐array is a well‐known data structure to implement the trie. However, the space efficiency of the double‐array degrades with the number of key deletions because the double‐array keeps empty elements produced by the key deletion. This paper presents a fast and compact elimination method of empty elements using properties of the trie nodes that have no siblings. The present elimination method is implemented by C language. From simulation results for large sets of keys, the present elimination method is about 30–330 times faster than the conventional elimination method and maintains high space efficiency. Copyright © 2003 John Wiley & Sons, Ltd.     

Current dependence of performance of TES microcalorimeters and characteristics of excess noise

We are developing transition edge sensor (TES) microcalorimeter arrays for future Japanese astronomy missions. Although 6.6 eV energy resolution for 5.9 keV and 74 μs decay time are achieved, our energy resolution was limited by the excess noise of unknown origin. The dominant noise showed 1/R dependence and it only appeared when the current through the TES, I, is larger than 10 μA. This is explained if we assume a constant voltage noise source with a level of 2(4kT_CR_n)^1/2. We also investigated the influence of I on the TES performance and found the TES sensitivity is reduced when the ratio of current to the critical current I/I_C is large. It can explain the reduction of observed when operated without a magnetic shield. We also found a strong correlation between I_C and or the baseline width. Thus, we conclude that I_C is an essential parameter for the TES performance.     

Suppression of active-oxidation of Si-C fibers (Hi-Nicalon) under reduced pressure by carbon or silica coating

The suppression of the active-oxidation of Si-C fibers (Hi-Nicalon) by carbon or silica coating were investigated at 1773 K under a reduced pressure of 1.32 Pa, through mass change determination, XRD analysis, resistivity measurement, SEM observation and tensile test. The coating of carbon and silica were conducted by heat-treating at 1773 K in CO-CO₂ gas mixtures. After exposure under a reduced pressure, the carbon coating formed in pure CO gas remained almost perfect and the retained strength of 1.7 GPa was nearly identical to that in the as-heat treated state. On the other hand, the carbon coatings formed under other conditions and all the silica coatings were completely lost during vacuum exposure. The retained strengths were in the range of 0 to 1.6 GPa. The silica film was found to be ineffective for suppressing the active-oxidation during vacuum exposure.