Entropy Based Approach to Data Loss Reparation Through the Indeterminate Fine-Grained Parallel Computation

The new method of a gap recovery in symbol sequences is presented. A covering is combined from the suitable reasonably short strings of the parts of a sequence available for observation. Two criteria are introduced to choose the best covering. It must yield the maximum of entropy of a frequency dictionary developed over the sequence obtained due to the recovery, if an overlapping combined from the copies of strings from the available parts of the sequence exists. The second criterion identifies the best covering in case when one has to use any string to cover the gap; here the best covering must yield the minimum of specific entropy of the frequency dictionary developed over the available parts of the sequence against the one developed over the entire sequence obtained due to the recovery. Kirdin kinetic machine which is the ideal fine-grained structureless computer has been used to resolve the problem of the reconstruction of a gap in symbol sequence.     

Web-based systems design: a study of contemporary practices and an explanatory framework based on “method-in-action”

This paper reports the findings of a detailed study of Web-based systems design (WBSD) practices in Ireland based on data collected over a 3-year period (2002–2005), the objectives of which were to (1) contribute towards a richer understanding of the current “real-world” context of WBSD by characterising the profile of a typical project (team size, timeframe, nature of requirements, etc.) and identifying the key challenges, constraints, and imperatives (i.e. “mediating factors”) faced by Web-based system designers, and (2) understand how those contextual parameters and mediating factors influence the activity of WBSD as regards the selection and enactment of whatever design practices are therefore engaged (i.e. the use of methods, procedures, etc.). Data was gathered through a survey which yielded 165 usable responses, and later through a series of semi-structured qualitative interviews. Using grounded theory, an explanatory conceptual framework is derived, based on an extension of the “method-in-action” model, the application of which to WBSD has not been previously investigated in depth. It is proposed that this framework of WBSD issues is valuable in a number of ways to educators, researchers, practitioners, and method engineers.     

The spatial economics of geothermal district energy in a small, low-density town: a case study of Mammoth Lakes, California

This research focuses on the spatial economics of geothermal district energy (DE) systems that distribute hot fluids through a pipeline network to multiple thermal customers. We argue here that DE is held back by uncertainty about its economic feasibility when implemented in real places. DE works best with high urban densities, but in the US the best geothermal resources are in the less-populated west. Economic geography theory suggests that the optimal size of a DE firm's service area should depend on the trade-off between the economies of scale inherent in a large service area and the greater network development costs and heat loss involved in serving a large area. The HEATMAP© software program developed by Washington State University was used to study the feasibility of numerous scenarios for a proposed DE system in Mammoth Lakes, California. Results indicate that the core area of the town is large enough, dense enough, and in close enough proximity to the resource for profitable DE development. Proposed ski village developments would increase the thermal load density and significantly enhance its ability to remain competitive with other fuels, even in pessimistic sensitivity analyses regarding geothermal heat input costs, public participation, and retro-fitting costs.     

Delamination Resistant Zinc Alloys: Simple Concept and Results on the System Zinc‐Magnesium

Alloying zinc coatings with elements such as magnesium and titanium increases the corrosion resistance in industrial tests. Based on the fundamental mechanism of cathodic delamination, a simple concept how alloying zinc with specific elements might improve its resistance to cathodic delamination is presented in this paper. As an example, results concerning the delamination of a simple polymer from the zinc‐magnesium intermetallic MgZn₂ are presented. From electrode potential measurements obtained with the Scanning Kelvin Probe it can be concluded that cathodic delamination from this alloy is completely inhibited. This behaviour is attributed to the electronic properties of the magnesium‐rich oxidic passive layer, that inhibits the oxygen reduction reaction at the metal oxide/polymer interface.     

Chromaticity contour map of the RGB cube: A simple algorithm

A simple algorithm (amenable to spreadsheets) is described for plotting a luminance contour map of the color gamut of an additive‐primary display given the chromaticities of its primaries and screen white. Each contour of the plot represents (in either r,g or x,y coordinates) the polygon of intersection of the RGB cube with a plane of constant Y. Each vertex on a contour is an intersection of 1 of the 12 edges of the RGB cube with the constant‐Y plane. Feasibility of an edge as a vertex of the polygon is tested through comparison of the computed r,g coordinates with functions of the luminosity coefficients of the primaries. By ordering the RGB‐cube edges in a particular way prior to scanning them for feasibility, one is guaranteed to retrieve the vertices of any constant‐Y polygon in convex order. This fact facilitates plotting of the polygons.     

Multiagent learning using a variable learning rate

Learning to act in a multiagent environment is a difficult problem since the normal definition of an optimal policy no longer applies. The optimal policy at any moment depends on the policies of the other agents. This creates a situation of learning a moving target. Previous learning algorithms have one of two shortcomings depending on their approach. They either converge to a policy that may not be optimal against the specific opponents' policies, or they may not converge at all. In this article we examine this learning problem in the framework of stochastic games. We look at a number of previous learning algorithms showing how they fail at one of the above criteria. We then contribute a new reinforcement learning technique using a variable learning rate to overcome these shortcomings. Specifically, we introduce the WoLF principle, “Win or Learn Fast”, for varying the learning rate. We examine this technique theoretically, proving convergence in self-play on a restricted class of iterated matrix games. We also present empirical results on a variety of more general stochastic games, in situations of self-play and otherwise, demonstrating the wide applicability of this method.