Adoption of electronic options trading at the ISE

US brokerage firms have shown strong interest in a new alternative for trading of equity options since the 26 May 2000 launch of the International Securities Exchange (ISE), an all-electronic trading platform. Although the collective impact of these adoption decisions led to a successful launch and a formidable competitor to the four established options markets in the US, major brokerage firms differ widely in their usage and adoption rates.     

Material interface reconstruction

The paper presents an algorithm for material interface reconstruction for data sets where fractional material information is given as a percentage for each element of the underlying grid. The reconstruction problem is transformed to a problem that analyzes a dual grid, where each vertex in the dual grid has an associated barycentric coordinate tuple that represents the fraction of each material present. Material boundaries are constructed by analyzing the barycentric coordinate tuples of a tetrahedron in material space and calculating intersections with Voronoi cells that represent the regions where one material dominates. These intersections are used to calculate intersections in the Euclidean coordinates of the tetrahedron. By triangulating these intersection points, one creates the material boundary. The algorithm can treat data sets containing any number of materials. The algorithm can also create nonmanifold boundary surfaces if necessary. By clipping the generated material boundaries against the original cells, one can examine the error in the algorithm. Error analysis shows that the algorithm preserves volume fractions within an error range of 0.5 percent per material.     

Knowledge-directed Adaptation in Multi-level Agents

Most work on adaptive agents have a simple, single layerarchitecture. However, most agent architectures support three levels ofknowledge and control: a reflex level for reactive responses, a deliberatelevel for goal-driven behavior, and a reflective layer for deliberateplanning and problem decomposition. In this paper we explore agentsimplemented in Soar that behave and learn at the deliberate and reflectivelevels. These levels enhance not only behavior, but also adaptation. Theagents use a combination of analytic and empirical learning, drawing from avariety of sources of knowledge to adapt to their environment. We hypothesize that complete, adaptive agents must be able to learn across all three levels.     

Servers in SCADA applications

Data acquisition and supervisory control and data acquisition (SCADA) systems have evolved from mainframe-based systems to multilevel tiered systems to flat client-server architecture. This paper examines the necessity for this evolution and the technology that spurred it on. A rod mill is discussed as a case study     

Polarization Phase-Based Method For Material Classification In Computer Vision

A robust and accurate polarization phase-based technique for material classification is presented. The novelty of this technique is three-fold in (i) its theoretical development, (ii) application, and, (iii) experimental implementation. The concept of phase of polarization of a light wave is introduced to computer vision for discrimination between materials according to their intrinsic electrical conductivity, such as distinguishing conducting metals, and poorly conducting dielectrics. Previous work has used intensity, color and polarization component ratios. This new method is based on the physical principle that metals retard orthogonal components of light upon reflection while dielectrics do not. This method has significant complementary advantages with respect to existing techniques, is computationally efficient, and can be easily implemented with existing imaging technology. Experiments for real circuit board inspection, nonconductive and conductive glass, and, outdoor object recognition have been performed to demonstrate its accuracy and potential capabilities.     

Implementing the Double Bootstrap

The single bootstrap already is popular in economics, though the double bootstrap has better convergence properties. We discuss the theory and implementation of the double bootstrap, both with and without the pivotal transformation, and give detailed examples of each. One example is a nonlinear double bootstrap of a Cobb-Douglas production function, and explains the use of Gauss-Newton Regressions as a device to decrease computational time. Another example is double bootstrapping elasticities from a translog production function.     

Robust Estimation of Rotation Angles from Image Sequences Using the Annealing M-Estimator

A robust method is presented for computing rotation angles of image sequences from a set of corresponding points containing outliers. Assuming known rotation axis, a least-squares (LS) solution are derived to compute the rotation angle from a clean data set of point correspondences. Since clean data is not guaranteed, we introduce a robust solution, based on the M-estimator, to deal with outliers. Then we present an enhanced robust algorithm, called the annealing M-estimator (AM-estimator), for reliable robust estimation. The AM-estimator has several attractive advantages over the traditional M-estimator: By definition, the AM-estimator involves neither scale estimator nor free parameters and hence avoids instabilities therein. Algorithmically, it uses a deterministic annealing technique to approximate the global solution regardless of the initialization. Experimental results are presented to compare the performance of the LS, M- and AM-estimators for the angle estimation. Experiments show that in the presence of outliers, the M-estimator outperforms the LS estimator and the AM-estimator outperforms the M-estimator.     

Development of filter functions for protein-ligand docking.

Current docking methods can generate bound conformations of a ligand close to the experimentally observed structure of a protein-ligand complex. However, the scoring functions used to evaluate the potential solutions are not yet reliable enough at giving the highest ranks to the best structure predictions. One approach to this problem is the use of filter functions that are applied to all docked conformations to remove structures with certain energetically unfavorable properties. We present a computationally efficient scheme for such a postprocessing of docking results. For each of the conformations generated for a given protein-ligand complex, four properties are calculated: the fraction of the ligand volume buried inside the binding pocket, the size of lipophilic cavities along the protein-ligand interface, the solvent-accessible surface (SAS) of nonpolar parts of the ligand, and the number of close contacts between nonhydrogen-bonded polar atoms of the ligand and the protein. These four terms were used to filter out the majority of the calculated solutions and to rescore the remaining ones. On a test set of 32 protein-ligand complexes, this protocol significantly improves the accuracy of the structure predictions.