The Application of Marginal Analysis to the Economic Lot Scheduling Problem

Application of marginal analysis to the Economic Lot Scheduling Problem reduces the solution search to a simple systematic calculation and feasibility check. Compared with mathematical programming methods and heuristic approaches advocated previously, marginal analysis results in lower optimum cost solution with shorter optimum basic period lengths. For comparative purposes, data are included which allow evaluation of marginal analysis results with dynamic programming results of previous researchers.     

Characterization of interfacial reaction and chemical bonding features of LaOx/HfO2 stack structure formed on thermally-grown SiO2/Si(1 0 0)

A stack structure consisting of ～1.5 nm-thick LaO_x and ～4.0 nm-thick HfO₂ was formed on thermally grown SiO₂ on Si(1 0 0) by MOCVD using dipivaloymethanato precursors, and the influence of N₂ annealing on interfacial reaction for this stack structure was examined by using X-ray photoelectron spectroscopy and Fourier transform infrared attenuated total reflection. We found that compositional mixing between LaO_x and HfO₂ becomes significant from 600 °C upwards and that interfacial reaction between HfLa_yO_z and SiO₂ proceeds consistently at 1000 °C in N₂ ambience.     

Modeling of diffusive mass transport in micropores in cement based materials

In order to predict long-term leaching behavior of cement constituents for safety assessments of radioactive waste disposal, we modeled diffusive mass transport in micropores in cement based materials. Based on available knowledge on the pore structure, we developed a transport porosity model that enables us to estimate effective porosity available for diffusion (transport porosity) in cement based materials. We microscopically examined the pore structure of hardened cement pastes to partially verify the model. Effective diffusivities of tritiated water in hardened cement pastes were also obtained experimentally, and were shown to be proportional to the estimated transport porosity.     

Supercooled Barium Boric Oxide Melts: X-Ray Diffraction Measurements and Glass Formation

It is well-known that oxide melts easily form a glass state from a supercooled state; however, it is difficult for some oxides to transform to the glass state from the corresponding supercooled state. β-BaB₂O₄ (β-BBO) crystals are important materials for laser applications. The β-BBO crystal easily grows from the supercooled melt, and it is therefore difficult to form the BBO glass state. We attempted to make BBO glass by a containerless technique using the conical nozzle gas-jet levitation (CNL) method. We were successful in making BBO glass with a diameter of 2 mm from a highly supercooled melt without rapid quenching. In order to clarify the phase selection mechanism of the BBO melt, we performed high-energy X-ray (113.6 keV) diffraction experiments on the glassy and supercooled liquid BBO using the CNL technique at the BL04B2 beamline of SPring-8. From these experiments, the structure factor S ( Q ) of BBO glasses and supercooled melts were found to have almost the same features. From these S ( Q ), we obtained the radial distribution function T ( r )=4π rg ( r ). The analysis also showed that BBO glass and the BBO-supercooled melt have the same short-range distances. For phase selection between crystalline and glassy phases, we discuss a structure model of the BBO melt, including medium range structure based on the short-range structure obtained in this experiment.     

Molecular logic and computing

Molecular substrates can be viewed as computational devices that process physical or chemical 'inputs' to generate 'outputs' based on a set of logical operators. By recognizing this conceptual crossover between chemistry and computation, it can be argued that the success of life itself is founded on a much longer-term revolution in information handling when compared with the modern semiconductor computing industry. Many of the simpler logic operations can be identified within chemical reactions and phenomena, as well as being produced in specifically designed systems. Some degree of integration can also be arranged, leading, in some instances, to arithmetic processing. These molecular logic systems can also lend themselves to convenient reconfiguring. Their clearest application area is in the life sciences, where their small size is a distinct advantage over conventional semiconductor counterparts. Molecular logic designs aid chemical (especially intracellular) sensing, small object recognition and intelligent diagnostics.     

Realization of Dynamic Walking and Running of the Quadruped Using Neural Oscillator

In the present study we attempt to induce a quadruped robot to walk dynamically on irregular terrain and run on flat terrain by using a nervous system model. For dynamic walking on irregular terrain, we employ a control system involving a neural oscillator network, a stretch reflex and a flexor reflex. Stable dynamic walking when obstructions to swinging legs are present is made possible by the flexor reflex and the crossed extension reflex. A modification of the single driving input to the neural oscillator network makes it possible for the robot to walk up a step. For running on flat terrain, we combine a spring mechanism and the neural oscillator network. It became clear in this study that the matching of two oscillations by the spring-mass system and the neural oscillator network is important in order to keep jumping in a pronk gait. The present study also shows that entrainment between neural oscillators causes the running gait to change from pronk to bound. This finding renders running fairly easy to attain in a bound gait. It must be noticed that the flexible and robust dynamic walking on irregular terrain and the transition of the running gait are realized by the modification of a few parameters in the neural oscillator network.     

An associative memory model derived from cross-coupled Hopfield nets and its role in noise-space dynamics

In this paper, the association characteristics of cross-coupled Hopfield nets (CCHN) proposed as a modular neural network model are discussed analytically. In a CCHN, an arbitrary number of modules (Hopfield networks) can be mutually connected via feedforward networks called internetworks, whose output generates interactions among module networks. To evaluate the CCHN as a modular neural network, it has previously been applied to associative memory. Although its excellent association performance is supported by many simulation results, it is still difficult to compute the memory capacity exactly or to examine the dynamic properties rigorously, because CCHN information processing includes strong nonlinearity. Hence, as the first step to an analytical approach, this paper focuses on a single-module CCHN whose interaction is realized by a two-layered feedforward internetwork. In this case, the connection matrix of the CCHN degenerates into a single square-matrix, as does a conventional auto-association type of associative memory. Using eigenvalue analysis for the connection matrix, we reveal that the essential differences between the association characteristics of a CCHN and a conventional autocorrelation associative memory originate from dynamics in the noise-space that is the orthogonal complement of the subspace generated from memory patterns. ©1998 Scripta Technica, Electr Eng Jpn, 125(2): 27–34, 1998     

One-dimensional self-assembly of alkoxy-capped silicon nanoparticles

We demonstrate here a novel method for self-assembling in dimensional alignment the alkoxy-capped silicon nanoparticles synthesized through a room-temperature chemical route. The alkoxy-capped silicon nanoparticles were prepared via a reduction of silicon tetrachloride with sodium-naphthalide and subsequent surface capsulation with 1-octanol monolayers. In the present method, a sublimation process, which was employed as a final purification process for removing the residual naphthalene, influenced significantly on the final morphology of the resultant nanoparticles. Scanning transmission electron microscope (STEM) confirmed the spherical nanoparticles on a holey carbon grid after sublimation process, while only the fibril-like morphology just before sublimation process. In the former sample, the resultant particle size was measured by STEM to be about 9.5 nm +/- 3.4 nm. On the other hand, in the latter sample, the fibril-like structures were shaped by self-assembled silicon nanoparticles in dimensional alignment. The diameters and lengths of the fibril-like assemblies were approximately measured to be 10 to 20 nm and over 5 microm, respectively.     

Studies of self-organization processes in nanoporous alumina membranes by small-angle neutron scattering

We performed studies of the self-organization processes in nanoporous alumina membranes at initial and late stages of aluminum anodization by using scanning electron microscopy (SEM) and small-angle neutron scattering (SANS). SEM observations indicated three stages in the self-organization of nanopores in alumina: (1) nucleation of random nanopores with a broad radius distribution, (2) narrowing the radius distribution and (3) slow evolution of the nanoporous structure towards ordering of nanopores into large domains. SANS studies revealed orientational correlation between ordered domains of nanopores, which is characterized by a small misorientation angle. For the samples with high aspect ratios of nanopores, the SANS patterns showed azimuthal smearing, which was attributed to the redistribution of nanopores between the domains during their growth.     

Comparative performance analysis of stroke correspondence search methods for stroke-order free online multi-stroke character recognition

For stroke-order free online multi-stroke character recognition, stroke-to-stroke correspondence search between an input pattern and a reference pattern plays an important role to deal with the stroke-order variation. Although various methods of stroke correspondence have been proposed, no comparative study for clarifying the relative superiority of those methods has been done before. In this paper, we firstly review the approaches for solving the stroke-order variation problem. Then, five representative methods of stroke correspondence proposed by different groups, including cube search (CS), bipartite weighted matching (BWM), individual correspondence decision (ICD), stable marriage (SM), and deviation-expansion model (DE), are experimentally compared, mainly in regard of recognition accuracy and efficiency. The experimental results on an online Kanji character dataset, showed that 99.17%, 99.17%, 96.37%, 98.54%, and 96.59% were attained by CS, BWM, ICD, SM, and DE, respectively as their recognition rates. Extensive discussions are made on their relative superiorities and practicalities.