The Agile particle swarm optimizer applied to proteomic pattern matching and discovery

Pattern discovery in protein structures is a fundamental task in computational biology, with important applications in protein structure prediction, profiling and alignment. We propose a novel approach for pattern matching and discovery in protein structures using particle swarm-based flying windows over potentially promising regions of the search space. Using a heuristic search, based on particle swarm optimization is, however, easily trapped in local optima due to the sparse nature of the problem search space. Thus, we introduce a novel fitness-based stagnation detection technique that effectively and efficiently restarts the search process to escape potential local optima. The proposed approach predicts an imminent stagnation situation using a novel way that collectively incorporates the already-calculated fitness performances of the swarm particles relative to the objective function, instead of repeatedly calculating their pairwise distances. Our approach is first applied to protein contact maps, which are the 2D compact representation of protein structures. Then, it is generalized to work on classical and advanced (shifted/rotated) benchmark optimization functions. The experimental results show that the proposed fitness-based approach not only demonstrates efficient convergence (up to 3 times faster), but also significantly outperforms the commonly used distance-based method (using Wilcoxon rank-sum test at 95 % confidence level).     

基于JTBC开发蒙古文网站内容管理系统的研究

本文提出基于"语言/代码/程序"两两分离的JTBC系统进行二次开发蒙古文网站内容管理系统的思路,就蒙古文网站内容管理系统开发的关键问题如蒙古文字体的显示、特殊的排版要求、所见即所得的后台编辑等进行对比研究,并对系统开发的整体解决方案进行论述.     

Graph-based tools for microscopic cellular image segmentation

We propose a framework of graph-based tools for the segmentation of microscopic cellular images. This framework is based on an object oriented analysis of imaging problems in pathology. Our graph tools rely on a general formulation of discrete functional regularization on weighted graphs of arbitrary topology. It leads to a set of useful tools which can be combined together to address various image segmentation problems in pathology. To provide fast image segmentation algorithms, we also propose an image simplification based on graphs as a pre processing step. The abilities of this set of image processing discrete tools are illustrated through automatic and interactive segmentation schemes for color cytological and histological images segmentation problems.     

How Software Developers Use Tagging to Support Reminding and Refinding

Developers frequently add annotations to source code to help them remember pertinent information and mark locations of interest for future investigation. Finding and refinding these notes is a form of navigation that is integral to software maintenance. Although there is some tool support in modern development environments for authoring and navigating these comments, we have observed that these annotations often fail to remind and are sometimes difficult to find by the programmer. To address these shortcomings, we have designed a new approach for software navigation called Tags for Software Engineering Activities (TagSEA). TagSEA combines the notion of waypointing (a mechanism for marking locations in spatial navigation) with social tagging to support programmers in defining semantically rich annotations to source code comments. The tool provides support for creating, editing, navigating, and managing these annotations. We present the results from two empirical studies, where we observed and then analyzed how professional programmers used source code annotations to support their development activities over 24 months. Our findings indicate that the addition of semantic information to annotations can improve their value. We also provide suggestions on how annotation tools in general may be improved.     

ASTM survey on uses and limitations of fire models

Current Research

ASTM survey on uses and limitations of fire models     

Variational Contrast Enhancement of Gray-Scale and RGB Images

The aim of this paper is twofold. First, we propose a new method for enhancing the contrast of gray-value images. We use the difference of the average local contrast measures between the original and the enhanced images within a variational framework. This enables the user to intuitively control the contrast level and the scale of the enhanced details. Moreover, our model avoids large modifications of the original image histogram. Thereby it preserves the global illumination of the scene and it can cope with large areas having similar gray values. The minimizer of the proposed functional is computed by a gradient descent algorithm in connection with a polynomial approximation of the average local contrast measure. The polynomial approximation is computed via Bernstein polynomials. In the second part, the approach is extended to a variational enhancement method for color images. The model approximately preserves the hue of the original image and additionally includes a total variation term to correct the possible noise. The method requires no post-  or preprocessing. The minimization problem is solved with a hybrid primal–dual algorithm. Experiments demonstrate the efficiency and the flexibility of the proposed approaches in comparison with state-of-the-art methods.     

Leveraging machine-learned detectors of systematic inquiry behavior to estimate and predict transfer of inquiry skill

We present work toward automatically assessing and estimating science inquiry skills as middle school students engage in inquiry within a physical science microworld. Towards accomplishing this goal, we generated machine-learned models that can detect when students test their articulated hypotheses, design controlled experiments, and engage in planning behaviors using two inquiry support tools. Models were trained using labels generated through a new method of manually hand-coding log files, “text replay tagging”. This approach led to detectors that can automatically and accurately identify these inquiry skills under student-level cross-validation. The resulting detectors can be applied at run-time to drive scaffolding intervention. They can also be leveraged to automatically score all practice attempts, rather than hand-classifying them, and build models of latent skill proficiency. As part of this work, we also compared two approaches for doing so, Bayesian Knowledge-Tracing and an averaging approach that assumes static inquiry skill level. These approaches were compared on their efficacy at predicting skill before a student engages in an inquiry activity, predicting performance on a paper-style multiple choice test of inquiry, and predicting performance on a transfer task requiring data collection skills. Overall, we found that both approaches were effective at estimating student skills within the environment. Additionally, the models’ skill estimates were significant predictors of the two types of inquiry transfer tests.     

压电体的混合变分原理及叠层板的自由振动分析

建立了具有机一电耦合效应的压电材料修正后的Hellinger—Reissner(H—R)混合变分原理，并推导了压电材料的Hamilton正则方程，即压电材料自由振动的控制微分方程；根据矩阵分析理论给出了带有压电材料层的叠层矩形板自由振动的精确求解方法，文中没有引入任何位移模式或应力模式假设，实例分析得到了压电混合叠层板正逆效应两种情况自由振动的低阶频率，并与已有文献结果进行了比较。本文提出的压电材料修正后的H—R混合变分原理将有利于压电材料动力问题的有限元法或半解析法的推导。     

Determination of mechanical behavior of natural fibre based hybrid composites experimentally

This paper deals with the production and the mechanical testing of natural fibre‐based hybrid composites. Hybrid composite is produced by vacuum assisted resin infusion method of woven jute fabric and nonwoven wool felt along with glass fabric. Tensile, flexure and impact properties have been evaluated and compared. The tensile strength and the Young's modulus were found to be 70.66 MPa and is 5.63 GPa, respectively. Flexure and impact tests were performed on both woven jute fabric surface and on nonwoven wool felt surface of the composite specimens. The highest flexural strength was obtained in the specimen loaded at the woven jute fabric surface. Impact test results show that the specimens impacted at the nonwoven wool felt surface were carrying higher loads than the specimens impacted at the woven jute fabric surface.     

Photoelectrochemical properties of lead-free ferroelectric ceramic Ba(Ti<Subscript>0.96</Subscript>Mg<Subscript>0.013</Subscript>Nb<Subscript>0.026</Subscript>)O<Subscript>3</Subscript>: application to solar conversion of eosin

The lead-free Ba(Ti_0.96Mg_0.013Nb_0.026)O₃ composition has been prepared by solid state reaction. The room temperature X-ray diffraction revealed a perovskite phase with a tetragonal symmetry. The complex dielectric permittivity measured on cooling from 470 to 150 K in the frequency range (10²–10⁶ Hz) indicated a ferroelectric behavior and exhibited a large electromechanical response. This ferroelectric perovskite showed photoelectrochemical properties with an optical gap of 2.90 eV, n-type conduction and a flat band potential of ?0.57 V _SCE . As application, the oxide is successfully tested for the eosin oxidation under solar light. At pH ~ 6.3, 90 % of eosin (15 mg L^?1) disappeared after 6 h of illumination for a catalyst dose of 2.5 g L^?1.