Stabilized Plane and Axisymmetric Lobatto Finite Element Models

High order elements are renowned for their high accuracy and convergence. Among them, Lobatto spectral finite elements are commonly used in explicit dynamic analyses as their mass matrices when evaluated by the Lobatto integration rule are diagonal. While there are numerous advanced first and second order elements, advanced high order elements are rarely seen. In this paper, generic stabilization schemes are devised for the reduced integrated plane and axisymmetric elements. Static and explicit dynamic tests are considered for evaluating the relatively merits of the stabilized and conventional elements. The displacement errors of the stabilized elements are less than those of the conventional Lobatto elements. When the material is nearly incompressible, the stabilized elements are also more accurate in terms of the energy error norm. This advantage is of practical importance for bio-tissue and hydrated soil analyses.postprin

Variational Inference-based Joint Interference Mitigation and OFDM Equalization Under High Mobility

In OFDM-based spectrum sharing networks, due to inefficient coordination or imperfect spectrum sensing, the signals from femtocells or secondary users appear as interference in a subset of subcarriers of the primary systems. Together with the inter-carrier interference (ICI) introduced by high mobility, equalizing one subcarrier now depends not only on whether interference exists, but also the neighboring subcarrier data. In this letter, we propose a novel approach to iteratively learn the statistics of noise plus interference across different subcarriers, and refine the soft data estimates of each subcarrier based on the variational inference. Simulation results show that the pro- posed method avoids the error floor effect, which is exhibited by existing algorithms without considering interference mitigation, and performs close to the ideal case with perfect ICI cancelation and knowledge of noise plus interference powers for optimal maximum a posteriori probability (MAP) equalizer.published_or_final_versio

An endophytic Taxol-producing fungus BT2 isolated from Taxus chinensis var. mairei

BT2, a newly isolated endophytic fungus from Taxus chinensis var. mairei, was observed to produce Taxol. Besides Taxol, a potent anticancer drug, BT2 could also yield taxane baccatin III, which was an important intermediate for Taxol and semi-synthesis of Taxol in industry. The isolation of such a fungusmay provide a promising alterative approach to produce Taxol, and BT2 can serve as a potential material for fungus engineering to improve Taxol productio

Environmental impacts of mining the giant Panzhihua V-Ti magnetite deposit, SW China

Abstract in http://www.lpi.usra.edu/meetings/gold2001/pdf/3530.pd

Filtering electrocardiographic signals using an unbiased and normalized adaptive noise reduction system

We present a novel unbiased and normalized adaptive noise reduction (UNANR) system to suppress random noise in electrocardiographic (ECG) signals. The system contains procedures for the removal of baseline wander with a two-stage moving-average filter, comb filtering of power-line interference with an infinite impulse response (IIR) comb filter, an additive white noise generator to test the system's performance in terms of signal-to-noise ratio (SNR), and the UNANR model that is used to estimate the noise which is subtracted from the contaminated ECG signals. The UNANR model does not contain a bias unit, and the coefficients are adaptively updated by using the steepest-descent algorithm. The corresponding adaptation process is designed to minimize the instantaneous error between the estimated signal power and the desired noise-free signal power. The benchmark MIT-BIH arrhythmia database was used to evaluate the performance of the UNANR system with different levels of input noise. The results of adaptive filtering and a study on convergence of the UNANR learning rate demonstrate that the adaptive noise-reduction system that includes the UNANR model can effectively eliminate random noise in ambulatory ECG recordings., leading to a higher SNR improvement than that with the same system using the popular least-mean-square (LMS) filter. The SNR improvement provided by the proposed UNANR system was higher than that provided by the system with the LMS filter, with the input SNR in the range of 5-20 dB over the 48 ambulatory ECG recordings tested. Crown Copyright (C) 2008 Published by Elsevier Ltd on behalf of IPEM. All rights reserved

Sheet metal plate design: a structured approach to product optimization in the presence of technological constraints

Geometrical optimization of structural components is a topic of high interest for engineers involved with design activities mainly related to mass reduction. The study described in these pages focuses on the optimization of plates subjected to bending for which stiffness is obtained by a pattern of ribs. Although stiffening by means of ribs is a well-known and old technique, the design of ribs for maximum stiffness is often based on practice and experience. Classical optimization methods such as topological, topographical and parametric optimization fail to give an efficient design with a reasonable programming effort, especially when dealing with many and complex constraints. These constraints are both technical and technological. A most promising technique to obtain optimal rib patterns was to define a set of feasible rib trajectories and then to select the subset with the most efficient combinations. The result is not unique and a method to select the optimal patterns is required. In fact, the stiffening effect increases with increasing rib length, but at a greater cost. A trade-off must be found between structural performance and cost: The tools to guide this selection process is the main objective of the paper, with particular attention in evaluating the stiffening due to the presence of beads on the plate with a close link with the production system and possible technological constraints which can occur during manufacturing processes, such as minimum rib distance or the presence of discontinuities or the presence of holes or other elements on the plate. A special tool with enforced rib cross section is considered, and optimal rib deployment has to be found. Numerical examples attached show the methodology and obtainable results. \ua9 2011 Springer-Verlag London Limited

Mesoscale modeling and simulation of microstructure evolution during dynamic recrystallization of a Ni-based superalloy

Microstructural evolution and plastic flow characteristics of a Ni-based superalloy were investigated using a simulative model that couples the basic metallurgical principle of dynamic recrystallization (DRX) with the twodimensional (2D) cellular automaton (CA). Variation of dislocation density with local strain of deformation is considered for accurate determination of the microstructural evolution during DRX. The grain topography, the grain size and the recrystallized fraction can be well predicted by using the developed CA model, which enables to the establishment of the relationship between the flow stress, dislocation density, recrystallized fraction volume, recrystallized grain size and the thermomechanical parameters

Tag-Aware Recommender Systems: A State-of-the-art Survey

In the past decade, Social Tagging Systems have attracted increasing attention from both physical and computer science communities. Besides the underlying structure and dynamics of tagging systems, many efforts have been addressed to unify tagging information to reveal user behaviors and preferences, extract the latent semantic relations among items, make recommendations, and so on. Specifically, this article summarizes recent progress about tag-aware recommender systems, emphasizing on the contributions from three mainstream perspectives and approaches: network-based methods, tensor-based methods, and the topic-based methods. Finally, we outline some other tag-related works and future challenges of tag-aware recommendation algorithms.Comment: 19 pages, 3 figure

Leaf image retrieval using a shape based method

For content-based image retrieval, shape information is of great importance. This paper presents a shape descriptor of imaged leaf objects according to their boundaries for image retrieval. We take picture of leaves, exact the sketch from original images and produce a low dimensional feature vector to describe the shape. By comparing the similarity of the query image with those in database, a set of images with shape similarity are retrieved. The experiment shows that the method has high reliability and less time consuming