Corrugated all-composite sandwich structures. Part 1: Modeling

An analytical model for the compressive and shear response of monolithic and hierarchical corrugated composite cores has been developed. The stiffness model considers the contribution in stiffness from the bending- and the shear deformations of the core members in addition to the stretching deformation. The strength model is based on the normal stress and shear stress distribution over each core member when subjected to a shear or compressive load condition. The strength model also accounts for initial imperfections. In part 1 of this series, the analytical model is described and the results are compared to finite element predictions. In part 2, the analytical model is compared to experimental results and the behaviour of the corrugated structures is investigated more thoroughly using failure mechanism maps. © 2008 Elsevier Ltd. All rights reserved.

Modeling the carbon nanofiber addressed liquid crystal microlens array from experimentally observed optical phenomena

This paper presents a novel method of using experimentally observed optical phenomena to reverse-engineer a model of the carbon nanofiber-addressed liquid crystal microlens array (C-MLA) using Zemax. It presents the first images of the optical profile for the C-MLA along the optic axis. The first working optical models of the C-MLA have been developed by matching the simulation results to the experimental results. This approach bypasses the need to know the exact carbon nanofiber-liquid crystal interaction and can be easily adapted to other systems where the nature of an optical device is unknown. Results show that the C-MLA behaves like a simple lensing system at 0.060-0.276 V/μm. In this lensing mode the C-MLA is successfully modeled as a reflective convex lens array intersecting with a flat reflective plane. The C-MLA at these field strengths exhibits characteristics of mostly spherical or low order aspheric arrays, with some aspects of high power aspherics. It also exhibits properties associated with varying lens apertures and strengths, which concur with previously theorized models based on E-field patterns. This work uniquely provides evidence demonstrating an apparent "rippling" of the liquid crystal texture at low field strengths, which were successfully reproduced using rippled Gaussian-like lens profiles. © 2014 Published by Elsevier B.V.

Gaussian processes for POMDP-based dialogue manager optimization

A partially observable Markov decision process (POMDP) has been proposed as a dialog model that enables automatic optimization of the dialog policy and provides robustness to speech understanding errors. Various approximations allow such a model to be used for building real-world dialog systems. However, they require a large number of dialogs to train the dialog policy and hence they typically rely on the availability of a user simulator. They also require significant designer effort to hand-craft the policy representation. We investigate the use of Gaussian processes (GPs) in policy modeling to overcome these problems. We show that GP policy optimization can be implemented for a real world POMDP dialog manager, and in particular: 1) we examine different formulations of a GP policy to minimize variability in the learning process; 2) we find that the use of GP increases the learning rate by an order of magnitude thereby allowing learning by direct interaction with human users; and 3) we demonstrate that designer effort can be substantially reduced by basing the policy directly on the full belief space thereby avoiding ad hoc feature space modeling. Overall, the GP approach represents an important step forward towards fully automatic dialog policy optimization in real world systems. © 2013 IEEE.

Achievements and challenges in machine vision-based inspection of large concrete structures

Large concrete structures need to be inspected in order to assess their current physical and functional state, to predict future conditions, to support investment planning and decision making, and to allocate limited maintenance and rehabilitation resources. Current procedures in condition and safety assessment of large concrete structures are performed manually leading to subjective and unreliable results, costly and time-consuming data collection, and safety issues. To address these limitations, automated machine vision-based inspection procedures have increasingly been proposed by the research community. This paper presents current achievements and open challenges in vision-based inspection of large concrete structures. First, the general concept of Building Information Modeling is introduced. Then, vision-based 3D reconstruction and as-built spatial modeling of concrete civil infrastructure are presented. Following that, the focus is set on structural member recognition as well as on concrete damage detection and assessment exemplified for concrete columns. Although some challenges are still under investigation, it can be concluded that vision-based inspection methods have significantly improved over the last 10 years, and now, as-built spatial modeling as well as damage detection and assessment of large concrete structures have the potential to be fully automated.

De novo RNA synthesis and homology modeling of the classical swine fever virus RNA polymerase

Classical swine fever virus (CSFV) non-structural protein 5B (NS5B) encodes an RNA-dependent RNA polymerase (RdRp), a key enzyme which initiates RNA replication by a de novo mechanism without a primer and is a potential target for anti-virus therapy. We expressed the NS5B protein in Escherichia coli. The rGTP can stimulate de novo initiation of RNA synthesis and mutation of the GDD motif to Gly-Asp-Asp (GAA) abolishes the RNA synthesis. To better understand the mechanism of viral RNA synthesis in CSFV, a three-dimensional model was built by homology modeling based on the alignment with several virus RdRps. The model contains 605 residues folded in the characteristic fingers, palm and thumb domains. The fingers domain contains an N-terminal region that plays an important role in conformational change. We propose that the experimentally observed promotion of polymerase efficiency by rGTP is probably due to the conformational changes of the polymerase caused by binding the rGTP. Mutation of the GDD to GAA interferes with the interaction between the residues at the polymerase active site and metal ions, and thus renders the polymerase inactive. (c) 2005 Elsevier B.V. All rights reserved.

An energy-efficient hopping robot based on free vibration of a curved beam

This paper explores a design strategy of hopping robots, which makes use of free vibration of an elastic curved beam. In this strategy, the leg structure consists of a specifically shaped elastic curved beam and a small rotating mass that induces free vibration of the entire robot body. Although we expect to improve energy efficiency of locomotion by exploiting the mechanical dynamics, it is not trivial to take advantage of the coupled dynamics between actuation and mechanical structures for the purpose of locomotion. From this perspective, this paper explains the basic design principles through modeling, simulation, and experiments of a minimalistic hopping robot platform. More specifically, we show how to design elastic curved beams for stable hopping locomotion and the control method by using unconventional actuation. In addition, we also analyze the proposed design strategy in terms of energy efficiency and discuss how it can be applied to the other forms of legged robot locomotion. © 1996-2012 IEEE.

Guided self-organization in a dynamic embodied system based on attractor selection mechanism

Guided self-organization can be regarded as a paradigm proposed to understand how to guide a self-organizing system towards desirable behaviors, while maintaining its non-deterministic dynamics with emergent features. It is, however, not a trivial problem to guide the self-organizing behavior of physically embodied systems like robots, as the behavioral dynamics are results of interactions among their controller, mechanical dynamics of the body, and the environment. This paper presents a guided self-organization approach for dynamic robots based on a coupling between the system mechanical dynamics with an internal control structure known as the attractor selection mechanism. The mechanism enables the robot to gracefully shift between random and deterministic behaviors, represented by a number of attractors, depending on internally generated stochastic perturbation and sensory input. The robot used in this paper is a simulated curved beam hopping robot: a system with a variety of mechanical dynamics which depends on its actuation frequencies. Despite the simplicity of the approach, it will be shown how the approach regulates the probability of the robot to reach a goal through the interplay among the sensory input, the level of inherent stochastic perturbation, i.e., noise, and the mechanical dynamics. © 2014 by the authors; licensee MDPI, Basel, Switzerland.

Study on Closed-set Speaker Identification Based on Biomimetic Pattern Recognition

In this paper, a new classifier of speaker identification has been proposed, which is based on Biomimetic pattern recognition (BPR). Distinguished from traditional speaker recognition methods, such as DWT, HMM, GMM, SVM and so on, the proposed classifier is constructed by some finite sub-space which is reasonable covering of the points in high dimensional space according to distributing characteristic of speech feature points. It has been used in the system of speaker identification. Experiment results show that better effect could be obtained especially with lesser samples. Furthermore, the proposed classifier employs a much simpler modeling structure as compared to the GMM. In addition, the basic idea "cognition" of Biomimetic pattern recognition (BPR) results in no requirement of retraining the old system for enrolling new speakers.

The image coding scheme based on neural network and SVM

This paper applies data coding thought, which based on the virtual information source modeling put forward by the author, to propose the image coding (compression) scheme based on neural network and SVM. This scheme is composed by "the image coding (compression) scheme based oil SVM" embedded "the lossless data compression scheme based oil neural network". The experiments show that the scheme has high compression ratio under the slightly damages condition, partly solve the contradiction which 'high fidelity' and 'high compression ratio' cannot unify in image coding system.

A highly efficient beam propagation method for modeling step-index waveguides with tilt interface

Based on a new finite-difference scheme and Runge-Kutta method together with transparent boundary conditions (TBCs), a novel beam propagation method to model step-index waveguides with tilt interfaces is presented. The modified scheme provides an precies description of the tilt interface of the nonrectangular waveguide structure, showing a much better efficiency and accuracy comparing with the previously presented formulas.

Optical constants of cubic GaN/GaAs(001): Experiment and modeling

The optical constants epsilon(E)=epsilon(1)(E)+iepsilon(2)(E) of unintentionally doped cubic GaN grown on GaAs(001) have been measured at 300 K using spectral ellipsometry in the range of 1.5-5.0 eV. The epsilon(E) spectra display a structure, associated with the critical point at E-0 (direct gap) and some contribution mainly coming from the E-1 critical point. The experimental data over the entire measured spectral range (after oxide removal) has been fit using the Holden-Munoz model dielectric function [M. Munoz et al., J. Appl. Phys. 92, 5878 (2002)]. This model is based on the electronic energy-band structure near critical points plus excitonic and band-to-band Coulomb-enhancement effects at E-0, E-0 + Delta(0) and the E-1, E-1 + Delta(1), doublet. In addition to evaluating the energy of the E-0 critical point, the binding energy (R-1) of the two-dimensional exciton related to the E-1 critical point was estimated using the effective mass/k.p theory. The line, shape of the imaginary part of the cubic-GaN dielectric function shows excitonic effects at room temperature not withstanding that the exciton was not resolved. (C) 2003 American Institute of Physics.

Modeling the dynamics of Si wafer bonding during annealing

The bonding behavior of silicon wafers depends on activation energy for the formation of siloxane bonds. In this article we developed a quantitative model on the dynamics of silicon wafer bonding during annealing. Based on this model, a significant difference in the bonding behaviors is compared quantitatively between the native oxide bonding interface and the thermal oxide bonding interface. The results indicate that the bonding strength of the native oxide interface increases with temperature much more rapidly than that of the thermal oxide interface. (C) 2000 American Institute of Physics. [S0021-8979(00)05520-1].

Kinetic modeling of N incorporation in GaInNAs growth by plasma-assisted molecular-beam epitaxy

We have studied the growth of GaInNAs by a plasma-assisted molecular-beam epitaxy (MBE). It was found that the N-radicals were incorporated into the epitaxial layer like dopant atoms. In the range of 400-500 degrees C, the growth temperature (T-g) mainly affected the crystal quality of GaInNAs rather than the N concentration. The N concentration dropped rapidly when T-g exceeded 500 degrees C. Considering N desorption alone is insufficient to account for the strong falloff of the N concentration with T-g over 500 degrees C, the effect of thermally-activated N surface segregation must be taken into account. The N concentration was independent of the arsenic pressure and the In concentration in GaInNAs layers, but inversely proportional to the growth rate. Based on the experimental results, a kinetic model including N desorption and surface segregation was developed to analyze quantitatively the N incorporation in MBE growth. (C) 2000 American Institute of Physics. [S0003-6951(00)00928-1].

Modeling and optimization of semiconductor manufacturing process with neural networks

A neural network-based process model is proposed to optimize the semiconductor manufacturing process. Being different from some works in several research groups which developed neural network-based models to predict process quality with a set of process variables of only single manufacturing step, we applied this model to wafer fabrication parameters control and wafer lot yield optimization. The original data are collected from a wafer fabrication line, including technological parameters and wafer test results. The wafer lot yield is taken as the optimization target. Learning from historical technological records and wafer test results, the model can predict the wafer yield. To eliminate the "bad" or noisy samples from the sample set, an experimental method was used to determine the number of hidden units so that both good learning ability and prediction capability can be obtained.

Generalized Viscoplastic Modeling of Debris Flow

Various concepts have been proposed or used in the development of rheological models for debris flow. The earliest model developed by Bagnold was based on the concept of the “dispersive” pressure generated by grain collisions. Bagnold’s concept appears to be theoretically sound, but his empirical model has been found to be inconsistent with most theoretical models developed from non-Newtonian fluid mechanics. Although the generality of Bagnold’s model is still at issue, debris-flow modelers in Japan have generally accepted Takahashi’s formulas derived from Bagnold’s model. Some efforts have recently been made by theoreticians in non-Newtonian fluid mechanics to modify or improve Bagnold’s concept or model. A viable rheological model should consist both of a rate-independent part and a rate-dependent part. A generalized viscoplastic fluid (GVF) model that has both parts as well as two major rheological properties (i.e., the normal stress effect and soil yield criterion) is shown to be sufficiently accurate, yet practical, for general use in debris-flow modeling. In fact, Bagnold’s model is found to be only a particular case of the GVF model. Analytical solutions for (steady) uniform debris flows in wide channels are obtained from the GVF model based on Bagnold’s simplified assumption of constant grain concentration.