An experimental investigation into the behavior of micro-bubbles flowing
through a micro-channel has been conducted. Experiments were performed within a
rectangular micro-channel with dimensions of 5 cm x 13.2 mm x l30 jim. Bubbles
were generated in an electrolyte solution by electrolysis at the lower channel wall near
the inlet....
Canopy structure has a significant impact on the canopy hydrology of
Douglas-fir forests in the Pacific Northwest (PNW). Whole canopy rainfall
interception was measured for young Douglas-fir forest and compared to an
old-growth Douglas-fir forest. The old-growth forest had significantly greater
canopy water storage capacity (5) and direct throughfall fraction...
It is difficult to build intelligent computer-aided design (ICAD) programs using available expert system shells and AI programming languages. To build ICAD programs, tools are needed that support (a) generative search of design spaces, (b) deep search of design spaces to evaluate alternative designs, (c) simultaneous exploration of alternative designs...
This report describes of current research in Artificial Intelligence at Oregon State University. The five areas of active research are ( a) intelligent aids for mechanical engineering design, (b) active experimentation as a method in machine learning, ( c) techniques for combining logic programming and assumption-based truth maintenance, ( d)...
The coverage of a learning algorithm is the number of concepts that can be learned by that algorithm from samples of a given size. This paper asks whether good learning algorithms can be designed by maximizing their coverage. The paper extends a previous upper bound on the coverage of any...
This paper applies learning techniques to make engineering optimization more efficient and reliable. When the function to be optimized is highly non-linear, the search space generally forms several disjoint convex regions . Unless gradient-descent search is begun in the right region, the solution found will be suboptimal. This paper formalizes...
Multiclass learning problems involve finding a definition for an unknown function f(x) whose range is a discrete set containing k > 2 values (i.e., k "classes") . The definition is acquired by studying large collections of training examples of the form (xi, f(xi)) . Existing approaches to this problem include...
Many important application problems can be formalized as constrained non-linear optimization tasks. However, numerical methods for solving such problems are brittle and do not scale well. Furthermore, they do not provide much insight into the structure of the problem space. This paper describes a method for discovering efficient rules that...