Policy Changes to the Federal and State Management of Subsistence Hunting and Fishing in Alaska

Subsistence in Alaska is currently being impacted by naturally occurring factors such as global warming, species migration shifts, and the declination of fishery and wildlife populations. Not only are external factors pressuring the debate, management strategies from the dual management operation appear to have failed. The current national focus has been centered on federal policy changes regarding subsistence. This project extends the federal subsistence review process into the state management of subsistence and provides practical solutions for enhancing both policy programs.

Review of Desalination and Concentrate Management Issues for Increasing Drinking Water Supplies

Water quantity and quality issues worldwide are causing nations to consider alternate sources for drinking water. Desalination and other membrane processes for treatment of seawater and brackish inland waters have been in use for the past quarter century and are growing in use worldwide. These treatment processes create a highly concentrated waste stream in which the principal constituents are dissolved solids. This report provides an overview of desalination methods and the methods available to dispose of this waste stream. Innovative technologies being studied for possible future use are also discussed.

Integrating the development of data mining and data warehouses via model-driven engineering

Data mining is one of the most important analysis techniques to automatically extract knowledge from large amount of data. Nowadays, data mining is based on low-level specifications of the employed techniques typically bounded to a specific analysis platform. Therefore, data mining lacks a modelling architecture that allows analysts to consider it as a truly software-engineering process. Bearing in mind this situation, we propose a model-driven approach which is based on (i) a conceptual modelling framework for data mining, and (ii) a set of model transformations to automatically generate both the data under analysis (that is deployed via data-warehousing technology) and the analysis models for data mining (tailored to a specific platform). Thus, analysts can concentrate on understanding the analysis problem via conceptual data-mining models instead of wasting efforts on low-level programming tasks related to the underlying-platform technical details. These time consuming tasks are now entrusted to the model-transformations scaffolding. The feasibility of our approach is shown by means of a hypothetical data-mining scenario where a time series analysis is required.

A Finite Element Numerical Algorithm for Modelling and Data Fitting in Complex Systems

Numerical modelling methodologies are important by their application to engineering and scientific problems, because there are processes where analytical mathematical expressions cannot be obtained to model them. When the only available information is a set of experimental values for the variables that determine the state of the system, the modelling problem is equivalent to determining the hyper-surface that best fits the data. This paper presents a methodology based on the Galerkin formulation of the finite elements method to obtain representations of relationships that are defined a priori, between a set of variables: y = z(x1, x2,...., xd). These representations are generated from the values of the variables in the experimental data. The approximation, piecewise, is an element of a Sobolev space and has derivatives defined in a general sense into this space. The using of this approach results in the need of inverting a linear system with a structure that allows a fast solver algorithm. The algorithm can be used in a variety of fields, being a multidisciplinary tool. The validity of the methodology is studied considering two real applications: a problem in hydrodynamics and a problem of engineering related to fluids, heat and transport in an energy generation plant. Also a test of the predictive capacity of the methodology is performed using a cross-validation method.