Set-based particle swarm optimization with status memory for knapsack problem

Set-based particle swarm optimization (S-PSO) operates on discrete space. S-PSO can solve combinatorial optimization problem with high quality and is successful to apply to the large-scale problem. In S-PSO, a velocity is a set with possibility and a position is a candidate solution. In this paper, we present a novel algorithm of set-based particle swarm optimization with status memory (S-PSOSM) to decide the position based on the previous position for solving knapsack problem. Some operators are redefined for S-PSOSM. S-PSOSM is a simple algorithm because the state of probability reduces. In addition, the weight of S-PSOSM is discussed. S-PSOSM shows high qualities in experimental results.     

Hierarchical learning from human preferences and curiosity

Applied Intelligence - Recent success in scaling deep reinforcement algorithms (DRL) to complex problems has been driven by well-designed extrinsic rewards, which limits their applicability to many...     

Ultra light-weight and high-resolution X-ray mirrors using DRIE and X-ray LIGA techniques for space X-ray telescopes

We are developing novel ultra light-weight and high-resolution X-ray micro pore optics for space X-ray telescopes. In our method, curvilinear micro pore structures are firstly fabricated by silicon deep reactive ion etching (DRIE) or X-ray LIGA processes. Secondly, side walls of the micro structures are smoothed by magnetic field assisted finishing and/or hydrogen annealing techniques for high reflectivity mirrors. Thirdly, to focus parallel X-ray lights from astronomical objects, these structures are elastically or plastically bent into a spherical shape. Fourthly, the bent structures are stacked to form a multi-stage X-ray telescope. In this paper, we report on fabrication and X-ray reflection tests of silicon and nickel X-ray mirrors using the DRIE and LIGA processes, respectively. For the first time, X-ray reflections were confirmed on both of the mirrors. Estimated rms roughnesses were 5 nm and 3 nm for the silicon and nickel mirrors, respectively.     

Thermodynamic evaluation of Cu– system based on newly determined Gibbs energy of formation of

Thermodynamic evaluation of Cu–Cu₃P system has been conducted by applying subregular solution model with Gibbs energy of Cu₃P formation that was newly determined by means of triple Knudsen cell mass spectrometry. Both the calculated vapor pressure of phosphorus and phase diagram of Cu–P system are excellently consistent with the literature data in the composition range of Cu–Cu₃P, indicating that there is no significant thermodynamic inconsistency between the present work based on the Gibbs energy of Cu₃P formation determined and the literature data.     

A new water-resistant snow index for the detection and mapping of snow cover on a global scale

An up-to-date spatio-temporal change analysis of global snow cover is essential for better understanding of climate–hydrological interactions. The normalized difference snow index (NDSI) is a widely used algorithm for the detection and estimation of snow cover. However, NDSI cannot discriminate between snow cover and water bodies without use of an external water mask. A stand-alone methodology for robust detection and mapping of global snow cover is presented by avoiding external dependency on the water mask. A new spectral index called water-resistant snow index (WSI) with the capability of exhibiting significant contrast between snow cover and other cover types, including water bodies, was developed. WSI uses the normalized difference between the value and hue obtained by transforming red, green, and blue, (RGB) colour composite images comprising red, green, and near-infrared bands into a hue, saturation, and value (HSV) colour model. The superiority of WSI over NDSI is confirmed by case studies conducted in major snow regions globally. Snow cover was mapped by considering monthly variation in snow cover and availability of satellite data at the global scale. A snow cover map for the year 2013 was produced at the global scale by applying the random walker algorithm in the WSI image supported by the reference data collected from permanent snow-covered and non-snow-covered areas. The resultant snow-cover map was compared to snow cover estimated by existing maps: MODIS Land Cover Type Product (MCD12Q1 v5.1, 2012), Global Land Cover by National Mapping Organizations (GLCNMO v2.0, 2008), and European Space Agency’s GlobCover 2009. A significant variation in snow cover as estimated by different maps was noted, and was was attributed to methodological differences rather than annual variation in snow cover. The resultant map was also validated with reference data, with 89.46% overall accuracy obtained. The WSI proposed in the research is expected to be suitable for seasonal and annual change analysis of global snow cover.     

Straight-through microchannel devices for generating monodisperse emulsion droplets several microns in size

The authors recently proposed a promising technique for producing monodisperse emulsions using a straight-through microchannel (MC) device composed of an array of microfabricated oblong holes. This research developed new straight-through MC devices with tens of thousands of oblong channels of several microns in size on a silicon-on-insulator plate, and investigated the emulsification characteristics using the microfabricated straight-through MC devices. Monodisperse oil-in-water (O/W) and W/O emulsions with average droplet diameters of 4.4–9.8 μm and coefficients of variation of less than 6% were stably produced using surface-treated straight-through MC devices that included uniformly sized oblong channels with equivalent diameters of 1.7–5.4 μm. The droplet size of the resultant emulsions depended greatly on the size of the preceding oblong channels. The emulsification process using the straight-through MC devices developed in this research had very high apparent energy efficiencies of 47–60%, defined as (actual energy input applied to droplet generation/theoretical minimum energy input necessary for making droplets) × 100. Straight-through MC devices with numerous oblong microfluidic channels also have great potential for increasing the productivity of monodisperse fine emulsions.     

Multiple kernel learning with gaussianity measures

Kernel methods are known to be effective for nonlinear multivariate analysis. One of the main issues in the practical use of kernel methods is the selection of kernel. There have been a lot of studies on kernel selection and kernel learning. Multiple kernel learning (MKL) is one of the promising kernel optimization approaches. Kernel methods are applied to various classifiers including Fisher discriminant analysis (FDA). FDA gives the Bayes optimal classification axis if the data distribution of each class in the feature space is a gaussian with a shared covariance structure. Based on this fact, an MKL framework based on the notion of gaussianity is proposed. As a concrete implementation, an empirical characteristic function is adopted to measure gaussianity in the feature space associated with a convex combination of kernel functions, and two MKL algorithms are derived. From experimental results on some data sets, we show that the proposed kernel learning followed by FDA offers strong classification power.     

Simulation research on monomer agglomeration of nonmetallic inclusions in steel with a diffusion limited aggregation model

The monomer agglomeration of nonmetallic inclusions was simulated with a diffusion limited aggregation （DLA） model of the fractal theory. The simulation study with a random two-dimensional diffusion was carried out. The results indicate that the DLA model can be used for the simulation of agglomeration behavior of the cluster-type inclusions. The morphology of clusters was observed with SEM and compared with the simulated agglomerates. The modelling procedure of the DLA model is applicable for the agglomeration process. The uncertainty of agglomeration process and the persuasive average agglomerative ratio was analyzed. The factors about the agglomerative ratio with the collision path distance and the size of particles or seed were discussed. The adherence of the nonmetallic inclusions on the dam, the weir and the walls of a tundish, and the absorption of inclusions by stopper or nozzle were also discussed.     

38. R&D on hydrogen production by high-temperature electrolysis of steam

One of the objectives of the high-temperature engineering test reactor (HTTR) is to demonstrate the effectiveness of high-temperature nuclear heat utilization, which aims to extend the application of nuclear heat to non-electric fields, especially to hydrogen production. As part of the development of the hydrogen production processes, laboratory-scale experiments of a high-temperature electrolysis of steam (HTES) had been carried out with a practical electrolysis tube with 12 solid-oxide cells connected in series. Using this electrolysis tube, hydrogen was produced at the maximum density of 44 N cm³/cm² h at a electrolysis temperature of 950 °C. Thereafter, to improve hydrogen production performance, a self-supporting planar electrolysis cell with a practical size (80 mm × 80 mm of electrolysis area) was fabricated. In the preliminary electrolysis experiment carried out at 850 °C, the planar cell produced hydrogen at the maximum density of 38 N cm³/cm² h, and the energy efficiency was almost as high as that obtained with the electrolysis tube at 950 °C. However, both electrolysis tubes and planar cells did not keep their integrity in one thermal cycle. Durability of the solid-oxide cell against the thermal cycle is one of the key issues of HTES.