Self-reflective segmentation of human bodily motions using recurrent neural networks

For realizing a naturalistic collaboration between the human and the robot, we have to establish the intention sharing from the series of motion data that are observed and exchanged between the human and the machine. In a word, this is a problem to detect "meanings" out of the digitized data stream. In this paper, we propose a novel approach based on semiosis, and present a method of interpreting bodily motions using recurrent neural networks called Elman networks. We made some experiments using the raw data acquired while a human performs a simple task of fetching objects by stretching and folding his/her arm, and demonstrate that the network can learn invariant features of the generalized motion concepts, classify the motion by referring to self-organized memory structure, and understand a task structure of the observed human bodily motion. These capabilities are essential for machine intelligence to establishing the human-robot shared autonomy, a new style of human-machine collaboration proposed in the area of robotics.     

Second harmonic generation from a ferroelectric film

We derive an expression for transmittivity (T_SHG) of second harmonic generation (SHG) signals from a ferroelectric (FE) film. Intensities of up and down fields in the medium are investigated in relation to T_SHG. The derivations are made based on undepletion of input fields and nonlinear wave equation derived from the Maxwell equations. We present two cases: film without mirrors and with partial mirrors. Expressions for the newly derived nonlinear susceptibility coefficients of SHG for real crystal symmetry [J. Opt. Soc. Am. B 19 (2002) 2007] are used to get more realistic results. Variations in T_SHG with respect to film thickness are illustrated.     

Gamma-irradiation-induced Ag/SiO2 composite films and their optical absorption properties

Small Ag particles or clusters dispersed mesoporous SiO₂ composite films were prepared by a new method: First the matrix SiO₂ films were prepared by sol-gel process combined with the dip-coating technique, then they were soaked in AgNO₃ solutions followed by irradiation of γ-ray at room temperature and in ambient pressure. The structures of these films were examined by X-ray diffraction (XRD), high-resolution transmission electron microscope (HRTEM), and optical absorption spectroscopy. It has been shown that the Ag particles grown within the porous SiO₂ films are very small, and they are isolated and dispersed from each other with very narrow size distributions. With increasing the soaking concentration and an additional annealing, an opposite peakshift effect of the surface plasmon resonance (SPR) was observed in the optical absorption measurements.     

Volumetric Change and Surface Properties of Temperature-Sensitive Polyvinylalcohol (PVA) Hydrogel

Polyvinylalcohol (PVA) polymer gel is a temperature sensitive polymeric gel, with a critical transition temperature (with H₂O) of 310 K. At higher than 310 K, this temperature sensitive polymer gel shrinks because of discharging water, whereas at lower temperatures, the gel swelled because of absorbing water. The reversibility of the gel's volume change was confirmed by temperature swing. The adsorption behavior of an organic compound onto the PVA polymer gel in water was tested at various temperatures. The amount of adsorbed organic compound increased remarkably at temperatures higher than about 310 K. Then, it was confirmed that the organic compound in PVA polymer gel could be reversibly adsorbed and desorbed by a temperature change between 293 and 323 K. The mechanism of adsorption of the organic compound onto the PVA polymer gel could be explained by hydration and dehydration of polymer gel.     

Classification of audio radar signals using radial basis function neural networks

Radial basis function (RBF) neural networks are used to classify real-life audio radar signals that are collected by a ground surveillance radar mounted on a tank. Currently, a human operator is required to operate the radar system to discern among signals bouncing off tanks, vehicles, planes, and so on. The objective of this project is to investigate the possibility of using a neural network to perform this target recognition task, with the aim of reducing the number of personnel required in a tank. Different signal classification methods in the neural net literature are considered. The first method employs a linear autoregressive (AR) model to extract linear features of the audio data, and then perform classification on these features, i.e, the AR coefficients. AR coefficient estimations based on least squares and higher order statistics are considered in this study. The second approach uses nonlinear predictors to model the audio data and then classifies the signals according to the prediction errors. The real-life audio radar data set used here was collected by an AN/PPS-15 ground surveillance radar and consists of 13 different target classes, which include men marching, a man walking, airplanes, a man crawling, and boats, etc. It is found that each classification method has some classes which are difficult to classify. Overall, the AR feature extraction approach is most effective and has a correct classification rate of 88% for the training data and 67% for data not used for training.     

Wavelength-tunable 40-GHz picosecond harmonically mode-locked fiber laser source

We demonstrate a novel 40-GHz mode-locked fiber laser that utilizes a single active device to provide both gain and mode-locking. The laser produces pulses as short as 2.2 ps, is tunable over a 27-nm band centered at 1553 nm, and exhibits long-term stability without cavity-length feedback control. The pulse train at 1556 nm was used in a 40-Gb/s transmission experiment over 45 km with a low 0.4-dB power penalty.     

Low-temperature post-treatment of anaerobically treated-sewage in anaerobic filter with cationic-polymer addition.

The post-treatment of domestic sewage pretreated in a 6 m3 UASB was investigated in two high-rate anaerobic filter (AF) reactors operated in parallel. The difference between the two AF reactors was only the addition of cationic polymer to the second reactor (AF + P). The reactors were operated at low temperatures, ranged between 13 and 20 degrees C. The media in each AF reactor consisted of vertical sheets of reticulated-polyurethane foam (RPF) with knobs. The results demonstrated that the AF + P reactor (HRT = 3 h) with cationic polymer addition (2 mg/L) was an efficient system for post-treatment. The removal efficiencies for total, suspended, colloidal and dissolved COD were, respectively, 41, 86 and 76 and 12% in the AF + P reactor and they were, respectively, 80, 97, 77 and 66% in the UASB + (AF + P) system. The removal of total, suspended and colloidal COD in the UASB + (AF + P) system were significantly higher than those achieved in the UASB + AF system. As hardly any nutrient was removed in the UASB + (AF + P) system, the effluent after pathogen removal is a valuable product for irrigation and fertilisation to close the water and nutrients cycle.     

Development of a Continuous Segmented Flow Tubular Reactor and the “Scale‐out” Concept – In Search of Perfect Powders

The synthesis of powders with controlled shape and narrow particle size distributions is still a major challenge for many industries. A continuous Segmented Flow Tubular Reactor (SFTR) has been developed to overcome homogeneity and scale‐up problems encountered when using batch reactors. Supersaturation is created by mixing the co‐reactants in a micromixer inducing precipitation; the suspension is then segmented into identical micro‐volumes by a non‐miscible fluid and sent through a tube. These micro‐volumes are more homogeneous when compared to large batch reactors leading to narrower size distributions, better particle morphology, polymorph selectivity and stoichiometry. All these features have been demonstrated on single tube SFTR for different chemical systems. To increase productivity for commercial application the SFTR is being “scaled‐out” by multiplying the number of tubes running in parallel instead of scaling‐up by increasing their size. The versatility of the multi‐tube unit will allow changes in type of precipitate with a minimum of new investment as new chemistry can be researched, developed and optimised in a single tube SFTR and then transferred to the multi‐tube unit for powder production.     

Reliability investigation of 0.07-/spl mu/m InGaAs-InAlAs-InP HEMT MMICs with pseudomorphic In/sub 0.75/Ga/sub 0.25/As channel

The authors have investigated the reliability performance of G-band (183 GHz) monolithic microwave integrated circuit (MMIC) amplifiers fabricated using 0.07-/spl mu/m T-gate InGaAs-InAlAs-InP HEMTs with pseudomorphic In/sub 0.75/Ga/sub 0.25/As channel on 3-in wafers. Life test was performed at two temperatures (T/sub 1/ = 200 /spl deg/C and T/sub 2/ = 215 /spl deg/C), and the amplifiers were stressed at V/sub ds/ of 1 V and I/sub ds/ of 250 mA/mm in a N/sub 2/ ambient. The activation energy is as high as 1.7 eV, achieving a projected median-time-to-failure (MTTF) /spl ap/ 2 /spl times/ 10/sup 6/ h at a junction temperature of 125 /spl deg/C. MTTF was determined by 2-temperature constant current stress using /spl Delta/G/sub mp/ = -20% as the failure criteria. The difference of reliability performance between 0.07-/spl mu/m InGaAs-InAlAs-InP HEMT MMICs with pseudomorphic In/sub 0.75/Ga/sub 0.25/As channel and 0.1-/spl mu/m InGaAs-InAlAs-InP HEMT MMICs with In/sub 0.6/Ga/sub 0.4/As channel is also discussed. The achieved high-reliability result demonstrates a robust 0.07-/spl mu/m pseudomorphic InGaAs-InAlAs-InP HEMT MMICs production technology for G-band applications.