Capability and limitation of max- and sum-type construction of Lyapunov functions for networks of iISS systems

This paper addresses the problem of verifying stability of networks whose subsystems admit dissipation inequalities of integral input-to-state stability (iISS). We focus on two ways of constructing a Lyapunov function satisfying a dissipation inequality of a given network. Their difference from one another is elucidated from the viewpoint of formulation, relation, fundamental limitation and capability. One is referred to as the max-type construction resulting in a Lipschitz continuous Lyapunov function. The other is the sum-type construction resulting in a continuously differentiable Lyapunov function. This paper presents geometrical conditions under which the Lyapunov construction is possible for a network comprising $n\ge 2$ subsystems. Although the sum-type construction for general $n>2$ has not yet been reduced to a readily computable condition, we obtain a simple condition of iISS small gain in the case of $n=2$. It is demonstrated that the max-type construction fails to offer a Lyapunov function if the network contains subsystems which are not input-to-state stable (ISS).     

Numerical study on the effect of heat loss upon the critical marangoni number in a half-zone liquid bridge

In a half-zone (HZ) liquid bridge, flow exhibits a transition from a two-dimensional steady to a three-dimensional oscillatory flow if the Marangoni number Ma exceeds a critical value Ma_c, or ΔT>ΔT_c. In case of high Prandtle number fluids, the Mac obtained in the numerical simulations deviated significantly from the ones by the experiments. One of the causes of the difference is due to the heat loss over the free surface. Most of past researches neglected effects of the heat loss through an interface of the liquid bridge. Recently several experimental and analytical works reported that the critical condition is significantly affected by the heat loss. The present study aims to include the effects of the heat loss upon the Ma_c. As the result, the calculated Ma_c agrees well with the experiment for a high Pr fluid.     

Microstructure and yield strength of UDIMET 720LI alloyed with Co-16.9 Wt Pct Ti

We proposed a new method for developing Ni-base turbine disc alloy for application at temperatures above 700 °C by mixing a Ni-base superalloy U720LI with a two-phase alloy Co-16.9 wt pct Ti in various contents. The microstructure and phase stability of the alloys were analyzed using an optical microscope, a scanning electron microscope, energy-dispersive spectroscopy, and an X-ray diffractometer. The yield strength was studied by compression tests at temperatures ranging from 25 °C to 1200 °C. The results show that all the alloys had a dendritic structure. Ni₃Ti (η) phase was formed in the interdendritic region in the alloys with the addition of Co-16.9 wt pct Ti, and its volume fraction increased with the increase in the addition of Co-16.9 wt pct Ti. The results of exposure at 750 °C show that the addition of Co-16.9 wt pct Ti to U720LI had a great effect on suppressing the formation of σ phase due to the reduced Cr content in the γ matrix. Compared to U720LI, the alloys with the addition of Co-16.9 wt pct Ti possessed higher yield strength. The solid-solution strengthening of γ and γ′ and higher volume fraction of γ′ were assumed to cause this strength increase.     

Study on Magnetic Responsibility of Rare Earth Ferrite／Polyacrylamide Magnetic Microsphere

Magneticpolymermicrospherecanbeseparatedquicklyundermagneticfieldandithasgotwideappli cationinmanyfields ,suchascellseparationetc .Themicrospheremustpossesshighmagneticresponsibili ty ,sothatmagneticseparationisquickandconve nient.Themagneticresponsibilit…     

A novel chromatographic separation technique using tertiary pyridine resin for the partitioning of trivalent actinides and lanthanides

A novel chromatographic separation technique using a tertiary pyridine type resin has been applied to the partitioning of the trivalent actinides (An) and lanthanides (Ln) and several successful results have been shown. In an alcoholic hydrochloric acid system, the trivalent An were clearly separated from the Ln, while no such group separation was achieved in an alcoholic nitric acid system. On the other hand, the nitric acid system was more effective for the intragroup (i.e. individual) separation of the trivalent An and the Ln than the hydrochloric acid system. On the basis of these results, a novel concept for the partitioning of the trivalent An and Ln using the present separation technique and its flowchart have been proposed with its advantages and disadvantages.     

Shaped silicon-crystal wafers obtained by plastic deformation and their application to silicon-crystal lenses.

Plastic deformation is an unlikely process by which to mould pristine silicon wafers into three-dimensional shapes owing to the inevitable detrimental impact that the resulting mechanically induced defects would have on their electrical properties. However, if one were to find a way of doing so without substantial degradation of these properties, a range of new applications might be opened up. Here we report on the successful plastic deformation of silicon crystal wafers for the preparation of wafers with various shapes. A silicon wafer was set between dies and pressed at high temperatures. One application of shaped wafers is as well-shaped concave silicon crystal lenses or mirrors. The lattice plane of such a crystal lens has a curvature exactly along the surface. A concave spheroidal X-ray lens, in the form of two-dimensional Johann and Johansson's monochromators, is proposed for an X-ray optical component system. We propose and demonstrate a new solar cell system with the concave silicon crystal mirror used as both a solar cell and a focused mirror. This system can make use of the reflected photons from solar cells.     

Effect of gravity on InGaSb crystal growth

The effect of gravity on dissolution of GaSb in InSb melt and growth of InGaSb was experimentally investigated. Experiments were carried out in a GaSb(seed)/InSb/GaSb(feed) sandwich system under an imposed temperature gradient. In the experiments, the GaSb feed crystal dissolved into the InSb melt to supply the required GaSb component for the growth of In_0.1Ga_0.9Sb crystal. Two parameters were considered: (1) the inclination angle (θ) of the sample for gravity as 0° and 53°, and (2) the sample diameter (D) as 9 mm and 5mm. When θ was 0°, the interface was almost flat, indicating that convection was axisymmetric and stable. Whereas the interface was distorted towards gravitational direction when θ was 53°, indicating that solutal convection was dominant. The decrease of growth temperature and sample diameter reduced the distortion of interface and the dissolution amount of GaSb feed. The homogeneous crystals were grown at the initial growth stage by supplying the GaSb component during growth.     

Three dimensional virtual crack closure-integral method (VCCM) with skewed and non-symmetric mesh arrangement at the crack front

In this paper, an extension of virtual crack closure-integral method (VCCM) for three dimensional linear fracture mechanics analysis using hexahedron finite elements is presented. In conventional three dimensional VCCM, there are some inherent requirements on the finite element model. They are (i) the faces of finite elements across the crack front have the same areas and (ii) they must be arranged symmetrically across the crack front. In present study, we developed a three dimensional VCCM without such requirements by considering work required to open one element face area whose shape is arbitrary. Though we assume the use of an ordinary 20 node serendipity element, present approach can be applied to other types of hexahedron elements.     

Complete Mining of Frequent Patterns from Graphs: Mining Graph Data

Basket Analysis, which is a standard method for data mining, derives frequent itemsets from database. However, its mining ability is limited to transaction data consisting of items. In reality, there are many applications where data are described in a more structural way, e.g. chemical compounds and Web browsing history. There are a few approaches that can discover characteristic patterns from graph-structured data in the field of machine learning. However, almost all of them are not suitable for such applications that require a complete search for all frequent subgraph patterns in the data. In this paper, we propose a novel principle and its algorithm that derive the characteristic patterns which frequently appear in graph-structured data. Our algorithm can derive all frequent induced subgraphs from both directed and undirected graph structured data having loops (including self-loops) with labeled or unlabeled nodes and links. Its performance is evaluated through the applications to Web browsing pattern analysis and chemical carcinogenesis analysis.     

A Knowledge Discovery System with Support for Model Selection and Visualization

The process of knowledge discovery in databases consists of several steps that are iterative and interactive. In each application, to go through this process the user has to exploit different algorithms and their settings that usually yield multiple models. Model selection, that is, the selection of appropriate models or algorithms to achieve such models, requires meta-knowledge of algorithm/model and model performance metrics. Therefore, model selection is usually a difficult task for the user. We believe that simplifying the process of model selection for the user is crucial to the success of real-life knowledge discovery activities. As opposed to most related work that aims to automate model selection, in our view model selection is a semiautomatic process, requiring an effective collaboration between the user and the discovery system. For such a collaboration, our solution is to give the user the ability to try various alternatives and to compare competing models quantitatively by performance metrics, and qualitatively by effective visualization. This paper presents our research on model selection and visualization in the development of a knowledge discovery system called D2MS. The paper addresses the motivation of model selection in knowledge discovery and related work, gives an overview of D2MS, and describes its solution to model selection and visualization. It then presents the usefulness of D2MS model selection in two case studies of discovering medical knowledge in hospital data—on meningitis and stomach cancer—using three data mining methods of decision trees, conceptual clustering, and rule induction.