Wood processing variables and adhesive joint performance

In order to obtain a bonded wood product from the tree, wood must be subjected to a series of processes. These include, among others, vital processes like drying of the green wood and machining of the surfaces of the dried wood in preparation for bonding. However, when wood is machined with dull blades, thermal degradation of the wood frequently occurs. The effects of kiln drying and thermal degradation of wood on the performance of the adhesive joints subsequently formed from such wood were investigated. Tapered double cantilever beam (TDCB) test specimens obtained from hard maple and phenol–resorcinol–formaldehyde (PRF) adhesives were used in the investigations. The enhancement of fracture energy due to the reduction in the moisture content of wood, the improved performance of adhesive joints due to rejointing of wood surfaces before bonding, and the reduction of adhesive joint strength resulting from thermal degradation of wood are presented and discussed.     

Lead acid battery storage model for hybrid energy systems

This paper describes a new battery model developed for use in time series performance models of hybrid energy systems. The model is intended to overcome some of the difficulties associated with currently used methods. It is based on the approach of chemical kinetics. This model, which can be used for charging and discharging, is specifically concerned with the apparent change in capacity as a function of charge and discharge rates. It assumes that the charge can be stored in two ways, either as immediately available or as chemically bound. As described in this paper, it requires the determination of as few as three constants. Examples of the deviation of the battery model constants and comparisons of the new model with those used previously are given. Based on the success of the new model, it has been incorporated into the latest versions of the University of Massachusetts's wind/diesel simulation codes.     

Degradation reduction in optics imagery using Toeplitz structure

This paper is concerned with improvement in optical image quality by image restoration. Image restoration is an ill-posed inverse problem which involves the removal or minimization of degradations caused by noise and blur in an image, resulting from, in this case, imaging through a medium. Our work here concerns the use of the underlying Toeplitz structure of such problems, and associated techniques for accelerating the convergence of iterative image restoration computations. Denoising methods, including total variation minimization, followed by segmentation-based preconditioning methods for minimum residual conjugate gradient iterations, are investigated. Regularization is accomplished by segmenting the image into (smooth) segments and varying the preconditioners across the segments. By taking advantage of the Toeplitz structure, our algorithms can be implemented with computational complexity of onlyO (ln ² logn), wheren ² is the number of pixels in the image andl is the number of segments used. Also, parallelization is straightforward. Numerical tests are reported for atmospheric imaging problems, including the case of spatially varying blur. Research supported in part by a National Science Foundation Postdoctoral Research Fellowship. Research sponsored by the U.S. Air Force Office of Scientific Research under grant F49620-97-1-1039. Research sponsored by the U.S. Air Force Office of Scientific Research under grant F49620-97-1-0139, and by the National Science Foundation under grant CCR-96-23356. Research sponsored by the National Science Foundation under grant CCR-96-23356.     

Potential applications of three-way multidimensional scaling and related techniques to integrate knowledge from multiple experts

Theknowledge transfer problem in artificial intelligence consists of finding effective ways to elicit information from a human expert and represent it in a form suitable for use by an expert system. One approach to formalizing and guiding this knowledge transfer process for certain types of expert systems is to use psychometric scaling methods to analyze data on how the human expert compares or groups solutions. For example, Butler and Corter [1] obtained judgments of thesubstitutability of solutions from an expert, then analyzed the resulting data via techniques for fitting trees and extended trees [2]. The expert's interpretation of certain aspects of the solutions were directly encoded as production rules, allowing rapid prototyping. In this paper we consider the problem of combining information from multiple experts. We propose the use of three-way or individual differences multidimensional scaling, tree-fitting, and unfolding models to analyze two types of data obtainable from the multiple experts: judgments of the substitutability of pairs of solutions, and judgments of the appropriateness of specific solutions to specific problems. An application is described in which substitutability data were obtained from three experts and analyzed using the SINDSCAL program [3] for three-way multidimensional scaling [4].     

Synthesis and material and electronic properties of conjugated polymers

Conjugated polymers such as polyacetylene are semiconductors, and can be chemically doped to give very high values of conductivity (up to 150 000 S cm^–1). The semiconducting properties are due to delocalization of the electron system formed along the polymer chain, and this general class of materials shows many desirable semiconductor properties for electrical and optical applications. There are considerable challenges to find synthetic routes to allow processing of the polymer to the forms required for applications, and many of the recent important advances in the field are due to improvements in this area.     

Protected completions of first-order general logic programs

Minker and Perlis [15] have made the important observation that in certain circumstances, it might be desirable to prevent the inference of A when A is in the finite failure set of a logic program P. In this paper, we investigate the model-theoretic aspects of their proposal and develop a Fitting-style [5] declarative semantics for protected completions of general logic programs (containing function symbols). This extends the Minker-Perlis proposal which applies to function-free pure logic programs. In addition, an operational semantics is proposed and it is proven to be sound for existentially quantified positive queries and negative ground queries to general, canonical protected logic programs. Completeness issues are investigated and completeness is proved for positive existential queries and negative ground queries for the following classes of programs: (1) function-free general protected logic programs (the Minker-Perlis operational semantics apply to function-free pure protected logic programs), (2) pure protected logic programs (with function symbols) and (3) protected general logic programs that do not contain any internal variables (though they may contain function symbols).     

Investigation of long term drift of an intraocular pressure sensor

Microsystem Technologies - “Zero drift” behavior of an optical intraocular pressure sensor is studied using an analytical model based on the deflection of a circular membrane. Results...     

Positive state‐bounding observer for positive interval continuous‐time systems with time delay

This paper is concerned with the problem of positive observer synthesis for positive systems with both interval parameter uncertainties and time delay. Conventional observers may no longer be applicable for such kind of systems due to the positivity constraint on the observers, and they only provide an estimate of the system state in an asymptotic way. A pair of positive observers with state‐bounding feature is proposed to estimate the state of positive systems at all times in this paper. A necessary and sufficient condition for the existence of desired observers is first established, and the observer matrices can be obtained easily through the solutions of a set of linear matrix inequalities (LMIs). Then, to reduce the error signal between the system state and its estimates, an iterative LMI algorithm is developed to compute the optimized state‐bounding observer matrices. Finally, a numerical example is presented to show the effectiveness and applicability of the theoretical results. Copyright © 2011 John Wiley & Sons, Ltd.     

Attention and visual memory in visualization and computer graphics

A fundamental goal of visualization is to produce images of data that support visual analysis, exploration, and discovery of novel insights. An important consideration during visualization design is the role of human visual perception. How we "see" details in an image can directly impact a viewer's efficiency and effectiveness. This paper surveys research on attention and visual perception, with a specific focus on results that have direct relevance to visualization and visual analytics. We discuss theories of low-level visual perception, then show how these findings form a foundation for more recent work on visual memory and visual attention. We conclude with a brief overview of how knowledge of visual attention and visual memory is being applied in visualization and graphics. We also discuss how challenges in visualization are motivating research in psychophysics.