Bioinformatics is central to biology education in the 21st century. With the generation of terabytes of data per day, the application of computer-based tools to stored and distributed data is fundamentally changing research and its application to problems in medicine, agriculture, conservation and forensics. In light of this 'information revolution,' undergraduate biology curricula must be redesigned to prepare the next generation of informed citizens as well as those who will pursue careers in the life sciences. The BEDROCK initiative (Bioinformatics Education Dissemination: Reaching Out, Connecting and Knitting together) has fostered an international community of bioinformatics educators. The initiative's goals are to: (i) Identify and support faculty who can take leadership roles in bioinformatics education; (ii) Highlight and distribute innovative approaches to incorporating evolutionary bioinformatics data and techniques throughout undergraduate education; (iii) Establish mechanisms for the broad dissemination of bioinformatics resource materials and teaching models; (iv) Emphasize phylogenetic thinking and problem solving; and (v) Develop and publish new software tools to help students develop and test evolutionary hypotheses. Since 2002, BEDROCK has offered more than 50 faculty workshops around the world, published many resources and supported an environment for developing and sharing bioinformatics education approaches. The BEDROCK initiative builds on the established pedagogical philosophy and academic community of the BioQUEST Curriculum Consortium to assemble the diverse intellectual and human resources required to sustain an international reform effort in undergraduate bioinformatics education.
Summary: Ka-me is a Voronoi image analyzer that allows users to analyze any image with a convex polygonal tessellation or any spatial point distribution by fitting Voronoi polygons and their dual, Delaunay triangulations, to the pattern. The analytical tools include a variety of graph theoretic and geometric tools that summarize the distribution of the numbers of edges per face, areas, perimeters, angles of Delaunay triangle edges (anglograms), Gabriel graphs, nearest neighbor graphs, minimal spanning trees, Ulam trees, Pitteway tests, circumcircles and convexhulls, as well as spatial statistics (Clark–Evans Nearest Neighborhood and Variance to Mean Ratio) and export functions for standard relationships (Lewis's Law, Desch's Law and Aboav–Weaire Law).Availability: Ka-me: a Voronoi image analyzer is available as an executable with documentation and sample applications from the BioQUEST Library (http://bioquest.org/downloads/kame_1.0.rar).Contact: noppadon.khiripet@nectec.or.th
This paper introduces an integrated methodology to monitor and diagnose machine faults in complex industrial processes such as textile and fiber manufacturing facilities. The approach is generic and applicable to a variety of industrial plants that operate critical processes and may require continuous monitoring and maintenance procedures. A dual approach is pursued: High-bandwidth fault symptomatic evidence, such as vibrations, current spikes, etc., are treated via a feature extractodneural network classifier construct while low-bandwidth phenomena, such as temperature, pressure, corrosion, leaks, etc., are better diagnosed with a fuzzy rule base set as an expert system. The technique is illustrated with typical examples from benchmark processes common to many industrial plants.
Abstract. Artists have long recognized that trees are self-similar across enormous differences in magnitudes; i.e., they share a common fractal structure -a trunk subdivides into branches which subdivide into more branches which eventually terminate in leaves, flowers, fruits, etc. Artistid Lindenmayer (1971, 1975, 1989, 1990) invented a mathematics based on graph grammar rewriting systems to describe such iteratively branching structures; these were named in honor of him and are referred to as L-systems. With the advent of fractals into computer graphics, numerous artists have similarly produced a wide variety of software packages to illustrate the beauty of fractal/Lsystem generated plants. Some tree visualizations such as L-Peach (Allen et al., 2005) do depend very explicitly upon a complex set of precise measurements of a single species of tree. Nonetheless, we felt that there is a need to build a package that allowed scientists (and students) to collect data from actual specimens in the field or laboratory, insert these measurements into an L-system package, and then visually compare actual trees to the computer generated image with such specimens. Furthermore, the effect of variance in parameters helps users evaluate the developmental plasticity both within and between species and varieties. We have developed 3D FractaL Tree (the L is capitalized in honor of Lindemayer) to generate trees based upon measurement of (1) relative lengths of two successive segments averaged over several iterations, (2) the angle theta between bifurcating limbs at successive joints, (3) the number of steps in branching that one must follow to find a branch extending at the same angle as the first one under consideration to determine the phyllotactic angle phi, (4) the average of the summed areas (determined from measurement of diameters) of bifurcations compared to the trunk to determine whether area of flow is preserved (and * Corresponding author. E-mail: jungck@beloit. Morphospace: measurement, modeling, mathematics, and meaning to consider Poiseuille's/Murray's law of laminar flow in a fractal network), (5) the total number of iterative branching from the base to the tip of tree averaged over several counts based on following out different major limbs, (6) an editable L-system rule chosen from a library of branching patterns that roughly correspond to a specimen under consideration, and (7) a degree of stochasticity applied to the above rules to represent some variation over the course of a lifetime. Of course, turned upside down, the computer imagery could be used to represent root structure instead of above ground growth or the bronchial system of a lung, for example. The measurements are recorded and analyzed in a series of worksheets in Microsoft Excel and the results are entered into the graphics engine in a Java application. 3D FractaL Tree produces a rotatable three-dimensional image of the tree which is helpful for examining such characters as self-avoidance (entanglement and breakage), reception of and penetration o...
Segmenting characters from mural images is a crucial basic operation for other tasks whose common goal is to preserve the mural art, one of the important Thai cultural heritage. The problem is effective segmentation algorithms, which are used at present, are semi-automatic and general purpose; so users have to put heavy effort to get the satisfied result. Hence this paper proposes the automatic segmentation algorithm to segment characters from mural images automatically. The algorithm is divided into two main parts: automatic selection part and segmentation part. In automatic selection, we applied spectral residual to play a key role in selecting regions of interest, i.e., an object region and a background region to be inputs of the segmentation part. In segmentation part, an iterated graph-cut is used as the main mechanism of the segmentation in this work. Besides, In order to improve performance of the iterated graphcuts, a superpixels algorithm is applied. Result of the algorithm from ordinary background images is 7.49% misclassified pixels with precision 73.02% and recall 94.64%.
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