Theoretical and evolutionary parameter tuning of neural oscillators with a double-chain structure for generating rhythmic signals

A neural oscillator with a double-chain structure is one of the central pattern generator models used to simulate and understand rhythmic movements in living organisms. However, it is difficult to reproduce desired rhythmic signals by tuning an enormous number of parameters of neural oscillators. In this study, we propose an automatic tuning method consisting of two parts. The first involves tuning rules for both the time constants and the amplitude of the oscillatory outputs based on theoretical analyses of the relationship between parameters and outputs of the neural oscillators. The second involves an evolutionary tuning method with a two-step genetic algorithm (GA), consisting of a global GA and a local GA, for tuning parameters such as neural connection weights that have no exact tuning rule. Using numerical experiments, we confirmed that the proposed tuning method could successfully tune all parameters and generate sinusoidal waves. The tuning performance of the proposed method was less affected by factors such as the number of excitatory oscillators or the desired outputs. Furthermore, the proposed method was applied to the parameter-tuning problem of some types of artificial and biological wave reproduction and yielded optimal parameter values that generated complex rhythmic signals in Caenorhabditis elegans without trial and error.     

A high‐performance sorting algorithm for multicore single‐instruction multiple‐data processors

Many sorting algorithms have been studied in the past, but there are only a few algorithms that can effectively exploit both single‐instruction multiple‐data (SIMD) instructions and thread‐level parallelism. In this paper, we propose a new high‐performance sorting algorithm, called aligned‐access sort (AA‐sort), that exploits both the SIMD instructions and thread‐level parallelism available on today's multicore processors. Our algorithm consists of two phases, an in‐core sorting phase and an out‐of‐core merging phase. The in‐core sorting phase uses our new sorting algorithm that extends combsort to exploit SIMD instructions. The out‐of‐core algorithm is based on mergesort with our novel vectorized merging algorithm. Both phases can take advantage of SIMD instructions. The key to high performance is eliminating unaligned memory accesses that would reduce the effectiveness of SIMD instructions in both phases. We implemented and evaluated the AA‐sort on PowerPC 970MP and Cell Broadband Engine platforms. In summary, a sequential version of the AA‐sort using SIMD instructions outperformed IBM's optimized sequential sorting library by 1.8 times and bitonic mergesort using SIMD instructions by 3.3 times on PowerPC 970MP when sorting 32 million random 32‐bit integers. Also, a parallel version of AA‐sort demonstrated better scalability with increasing numbers of cores than a parallel version of bitonic mergesort on both platforms. Copyright © 2011 John Wiley & Sons, Ltd.     

Breakdown Phenomena in Point-to-Point Gaps

Measurements with multiple techniques delineating the complete sequence of events from the primary streamer to the formation of the spark channel for relatively small point-to-point gaps are reported. The pulsed potential with 0.4 μs rise time and 1800 μs decay time was applied to the point-to-point gap, of which length was changed from 6 to 14 cm. The light pulses were observed by 5 photomultipliers as well as current and potential wave. It is shown that the spark channel can be materialized through the following three processes: 1) initial process, in which the primary, the secondary, and the tertiary streamers develop from both point electrodes into gap, and the ionizing wave bridges the gap; 2) intermediate process, in which the dark period proceeds with ion and electron movement if the applied potential is around the mean breakdown potential, or in the other case, the ``leader' develops from the anode with the help of ionizing waves; and 3) final process, in which the channel is highly ionized at first by the ionizing wave, then gas heating, to lead the formation of a spark channel. On the bases of the measurements of streamer speed and current, the ion and electron density were calculated. It is estimated that starting with the primary streamer with an electron density of 1012 cm-3, the electron density in the streamer channel is augmented by the ionizing wave up to 1012cm -3 when the gap is bridged by the ionizing wave.     

Theory of the excitonic fluctuation in a strong magnetic field. I. Development of the physical picture and a self-consistent Hartree theory

The physical picture of the appearance of the excitonic correlation in a strong magnetic field is developed in an electron-hole system which consists of one conduction band and one valence band. The field is assumed to be sufficiently strong that all the electrons and holes occupy their lowest Landau levels. Kinematical and dynamical aspects of such a truncated system are discussed in detail. The discussion does not deny the possibility of the excitonic phase transition in a strong magnetic field. The essence of the present physics is in the high degeneracy of the single-particle state and the strong shrinking of the electron wave function due to the magnetic field. In order to study the physics explicitly we construct a self-consistent Hartree theory. Further introducing static and local approximations for the excitonic fluctuation. We can determine the quasiparticle state and the fluctuation exactly near the transition point. We present the transition temperature in two limiting cases of the band configuration. We indicate the self-consistent Hartree theory combined with the static and local approximations is an unsatisfactory theory in the light of our physical picture. We also discuss possible improvements of the theory briefly.     

Helium gas permeability of montmorillonite/epoxy nanocomposites

Helium gas permeability of silicate clay (montmorillonite) particles/epoxy nanocomposites was examined. The incorporation of increasing amounts of montmorillonite particles reduced the helium gas permeability. Based on Fick’s law, gas permeation behavior of the nanocomposite was evaluated. With the increase of montmorillonite loading, gas diffusivity decreased, while gas solubility increased. Helium diffusion behavior is in agreement to the numerical results based on the Hatta–Taya–Eshelby theory. It has been revealed that dispersion of nanoscale platelets in polymer is effective in improving gas barrier property.     

Wide-gap layered oxychalcogenide semiconductors: Materials, electronic structures and optoelectronic properties

Applying the concept of materials design for transparent conductive oxides to layered oxychalcogenides, several p-type and n-type layered oxychalcogenides were proposed as wide-gap semiconductors and their basic optical and electrical properties were examined. The layered oxychalcogenides are composed of ionic oxide layers and covalent chalcogenide layers, which bring wide-gap and conductive properties to these materials, respectively. The electronic structures of the materials were examined by normal/inverse photoemission spectroscopy and energy band calculations. The results of the examinations suggested that these materials possess unique features more than simple wide-gap semiconductors. Namely, the layered oxychalcogenides are considered to be extremely thin quantum wells composed of the oxide and chalcogenide layers or 2D chalcogenide crystals/molecules embedded in an oxide matrix. Observation of step-like absorption edges, large band gap energy and large exciton binding energy demonstrated these features originating from 2D density of states and quantum size effects in these layered materials.     

Seismic proof test of a reinforced concrete containment vessel (RCCV): Part 2: Results of shaking table tests

A 1/8-scale model was constructed of a reinforced concrete containment vessel (RCCV) used in the latest advanced boiling water reactors (ABWR). Shaking table tests were conducted on it with input motions corresponding to or exceeding a design earthquake assumed for a real Nuclear Power Plant.The objectives of the tests were to verify the structural integrity and the leak-proof functional soundness of the RCCV subjected to design earthquakes, and to determine the ultimate strength and seismic margin by an excitation that led to the model's collapse. The model, the test sequence and the pressure and leak test results were addressed in Part 1. The shaking table test method, the input motions and the test results, including the transition of the model's stiffness, natural frequencies and damping factors and the effects of vertical input motions and internal pressure on the model's characteristics and behavior, the load–deformation, the ultimate strength, the failure mode of the reinforced concrete portion and the liner plate are described here. The seismic safety margin that was evaluated by the energy input during the failure test to a design basis earthquake will be described in Part 3. The analytical results of simulation using the multi-lumped mass model will be described in Part 4.     

Design and Analysis of Internet-Based Tele-Coordinated Multi-Robot Systems

The coordination of multi-robots is required in many scenarios for efficiency and task completion. Combined with teleoperation capabilities, coordinating robots provide a powerful tool. Add to this the Internet and now it is possible for multi-experts at multi-remote sites to control multi-robots in a coordinated fashion. For this to be feasible there are several hurdles to be crossed including Internet type delays, uncertainties in the environment and uncertainties in the object manipulated. In addition, there is a need to measure and control the quality of tele-coordination. To this end, the measure of force sensed by each robot is suggested and justified as a coordination index. It was proven that if n robots are event-transparent and event-synchronous then they can be teleoperated under random delay conditions to coordinate to any index value, which is feasible under no delay conditions. The design procedure that ensures a system can satisfy a small coordination index was presented and analyzed.In addition, the design and analysis of event-synchronous systems using Petri Nets is detailed. The Petri Net design methodology is presented for both event-synchronous single operator single robot teleoperation systems and event-synchronous multi-operator multi-robot teleoperation systems.The theory developed was tested by bilaterally tele-coordinating two mobile manipulators via the Internet. The experimental results confirmed the theoretical results presented.     

Reusing Primitive and Acquired Motion Knowledge for Gait Generation of a Six-legged Robot Using Genetic Programming

There has been growing interest in motion planning problems for mobile robots. In this field, the main research is to generate a motion for a specific robot and task without previously acquired motions. However it is too wasteful not to use hard-earned acquired motions for other tasks. Here, we focus on a mechanism of reusing acquired motion knowledge and study a motion planning system able to generate and reuse motion knowledge. In this paper, we adopt a tree-based representation for expressing knowledge of motion, and propose a hierarchical knowledge for realizing a reuse mechanism. We construct a motion planning system using hierarchical knowledge as motion knowledge and using genetic programming as a learning method. We apply a proposed method for the gait generation task of a six-legged locomotion robot and show its availability with computer simulation.     

Sensor Fusion System Using Recurrent Fuzzy Inference

In robotic and manufacturing systems, it is difficult to measure the state of systems accurately because of many uncertain factors and noise, and it is very important to estimate the state of systems. We must measure the phenomena of systems by multiple sensors and estimate the state of systems by acquiring information of sensors. However, we can not acquire all of sensor information synchronically, because each sensor has particular sensor information and measuring time. For estimating the state of systems by multiple sensors, a multi-sensor fusion system fusing various sensory information is needed. In this paper, we propose a Recurrent Fuzzy Inference (RFI) with recurrent inputs and apply it to a multi-sensor fusion system for estimating the state of systems. The membership functions of RFI are expressed by Radial Basis Function (RBF) with insensitive ranges. The shape of the membership functions can be adjusted by a learning algorithm. The learning algorithm is based on the steepest descent method and incremental learning which can add new fuzzy rules. The effectiveness of the multi-sensor fusion system using RFI will be shown through a numerical experiment of moving robot and estimation of surface roughness in grinding process.