Mobile robot control by neural networks using self-supervisedlearning

A reinforcement learning algorithm based on supervised learning is described. It uses associative search to discover and learn actions that make the system perform a desired task. One problem with associative search is that the system's actions are often inconsistent. In the searching process, the system's actions are always decided stochastically, so the system cannot perform learned actions more than once, even if they have been determined to be suitable actions for the desired task. To solve this problem, a neural network that can predict an evaluation of an action and control the influence of the stochastic element is used. Results from computer simulations using the algorithms to control a mobile robot are described     

Hot-carrier degradation of submicrometer p-MOSFETs withthermal/LPCVD composite oxide

It is shown that while gate oxides containing thermal/LPCVD composite oxide have lower defect densities than gates using only thermal oxides, they are more susceptible to hot-carrier degradation. The hot-carrier-induced degradation of composite oxides is worse in p-channel MOSFETs than in n-channel MOSFETs. This sensitivity of p-channel MOSFETs is caused by higher electron trapping levels in LPCVD oxides. For 150-Å gate technology, the hot-carrier-degradation resistance of thermal/LPCVD composite gate oxides with a 70-Å or thicker thermal oxide layer approaches that of high-quality pure thermal oxide     

Isotachophoretic analysis of surfactants

The qualitative and quantitative determination of anionic surfactants (sodium and lithium alkylsulfate, sodium dodecylbenzenesulfonate, sodium di-2-ethylhexyl sulfosuccinate, sodium and lithium perfluoroalkylcarboxylate, and lithium perfluorooctanesulfonate) were investigated by a capillary tube isotachophoresis using a potential gradient detector. The leading electrolyte solution was the mixture of acetonitrile and aqueous solution of histidine buffer containing calcium chloride. The terminating electrolyte solution was the aqueous solution of sodium octanoate. These electrolytes were effective for the analysis of the mixtures of strongly acidic surfactants.     

Buoyancy engine developed for underwater gliders

A buoyancy engine with a swashplate-type axial piston pump was developed. Its oil extrusion and drawing properties under high hydraulic pressure were evaluated. This buoyancy engine is now installed in an underwater glider that will achieve long-term monitoring of ocean environments up to 2100 m depth in a designated area with lower operational costs. This bidirectionally functioning pump can control the amount of oil in extrusion and draw operations. When drawing oil under high pressure, the hydraulic pump and the electric motor, respectively, act as a hydraulic motor and an electric generator. The generated electric power is absorbed by a damping resistor. The oil-drawing and extrusion properties were measured using a large hyperbaric chamber that is able to produce an almost identical environment to that of actual operations. Results confirmed stable oil extrusion operations up to 21 MPa. Regarding oil-drawing properties, although it was measured only up to 10 MPa in the hyperbaric chamber, it can be inferred that the system can draw the oil and can control the buoyancy precisely up to 21 MPa by replacing the two-way ball valve with an electromagnetic latching solenoid valve.     

Dual frequency open-loop electric potential microscopy for local potential measurements in electrolyte solution with high ionic strength

Recent development of open-loop electric potential microscopy (OL-EPM) has enabled to measure local potential distribution at a solid/liquid interface. However, the operating environment of OL-EPM has been limited to a weak electrolyte solution (<1 mM). This has significantly limited its application range in biology and chemistry. To overcome this limitation, we have developed dual frequency (DF) mode OL-EPM. In the method, an ac bias voltage consisting of two frequency components at f(1) and f(2) is applied between a tip and sample. The local potential is calculated from the amplitudes of the f(1) and |f(1) - f(2)| components of the electrostatic force. In contrast to the conventional single frequency (SF) mode OL-EPM, the detection of the 2f(1) component is not required in DF mode. Thus, the maximum bias modulation frequency in DF mode is twice as high as that in SF mode. The high bias modulation frequency used in DF mode prevents the generation of electrochemical reactions and redistribution of ions and water, which enables to operate OL-EPM even in a strong electrolyte solution. In this study, we have performed potential measurements of nanoparticles on a graphite surface in 1 and 10 mM NaCl solution. The results demonstrate that DF mode OL-EPM allows measurements of local potential distribution in 10 mM electrolyte solution.     

High-power CW deep-UV coherent light sources around 200 nm based on external resonant sum-frequency mixing

We report pure continuous-wave (CW) high-power (>100 mW) deep-ultraviolet (DUV) light sources emitting around 200-nm spectral region based on singly resonant sum-frequency mixing (SRSFM). Efficient DUV generation is made possible by use of a Brewster-cut CsLiB/sub 6/O/sub 10/ (CLBO) crystal near noncritically phase-matched (NCPM) condition for the SFM of 1-/spl mu/m output of neodymium lasers. The CW radiation of fifth-harmonic wavelength of a neodymium laser at 213 nm was generated by the SFM of enhanced 1064-nm radiation with single-passing 266-nm radiation produced by external-resonant frequency doubling of a 532-nm green laser. With 1.8 W of 266-nm radiation incident upon a CLBO crystal, as much as 180 mW of CW 213-nm power has been produced. The sub-200-nm CW radiation with 140-mW power has also been achieved by SFM of 1064 nm with 244-nm radiation from a frequency-doubled Argon-ion laser in the CLBO crystal operated near the NCPM condition.     

Boroxine Nanotubes: Moisture‐Sensitive Morphological Transformation and Guest Release

Boroxines, (R‐BO)₃, which can be easily synthesized via a dehydration reaction of boronic acids, R–B(OH)₂, selectively self‐assemble in toluene into nanofibers, nanorods, nanotapes, and nanotubes, depending on the aromatic substituent (R). Spectroscopic measurements show that the nanotube consists of a J‐aggregate of the boroxine. Humidification converts the morphology from the nanotube to a sheet as a result of the hydrolysis of the boroxine components and subsequent molecular‐packing rearrangement from the J‐aggregate to an H‐aggregate. Such a transformation leads to the compulsive release of guest molecules encapsulated in the hollow cylinder of the nanotube. The hydrolysis and the molecular‐packing rearrangement described above are suppressed by coordination of pyridine to the boron atom, with the resulting moiety acting as a Lewis acid of the boroxine component. The pyridine‐coordinated nanotube is transformed into a helical coil by humidification. Guest release during the nanotube‐to‐helical‐coil transformation is much slower than during the nanotube‐to‐sheet transformation, but faster than from a nanotube that did not undergo morphological transformation. The storage and release of guest molecules from the boroxine nanotubes can be precisely controlled by adjusting the moisture level and the concentration of Lewis bases, such as amines.     

Sparse LMS/F algorithms with application to adaptive system identification

Standard least mean square/fourth (LMS/F) is a classical adaptive algorithm that combined the advantages of both least mean square (LMS) and least mean fourth (LMF). The advantage of LMS is fast convergence speed while its shortcoming is suboptimal solution in low signal‐to‐noise ratio (SNR) environment. On the contrary, the advantage of LMF algorithm is robust in low SNR while its drawback is slow convergence speed in high SNR case. Many finite impulse response systems are modeled as sparse rather than traditionally dense. To take advantage of system sparsity, different sparse LMS algorithms with l_p‐LMS and l₀‐LMS have been proposed to improve adaptive identification performance. However, sparse LMS algorithms have the same drawback as standard LMS. Different from LMS filter, standard LMS/F filter can achieve better performance. Hence, the aim of this paper is to introduce sparse penalties to the LMS/F algorithm so that it can further improve identification performance. We propose two sparse LMS/F algorithms using two sparse constraints to improve adaptive identification performance. Two experiments are performed to show the effectiveness of the proposed algorithms by computer simulation. In the first experiment, the number of nonzero coefficients is changing, and the proposed algorithms can achieve better mean square deviation performance than sparse LMS algorithms. In the second experiment, the number of nonzero coefficient is fixed, and mean square deviation performance of sparse LMS/F algorithms is still better than that of sparse LMS algorithms. Copyright © 2013 John Wiley & Sons, Ltd.