Inverse Static Analysis of Massive Parallel Arrays of Three-State Actuators via Artificial Intelligence

Massive parallel robots (MPRs) driven by discrete actuators are force regulated robots that undergo continuous motions despite being commanded through a finite number of states only. Designing a real-time control of such systems requires fast and efficient methods for solving their inverse static analysis (ISA), which is a challenging problem and the subject of this thesis. In particular, five Artificial intelligence methods are proposed to investigate the on-line computation and the generalization error of ISA problem of a class of MPRs featuring three-state force actuators and one degree of revolute motion.

New algorithms for automated phylogenetic reconstruction using artificial intelligence and data mining techniques

Academic and industrial research in the late 90s have brought about an exponential explosion of DNA sequence data. Automated expert systems are being created to help biologists to extract patterns, trends and links from this ever-deepening ocean of information. Two such systems aimed on retrieving and subsequently utilizing phylogenetically relevant information have been developed in this dissertation, the major objective of which was to automate the often difficult and confusing phylogenetic reconstruction process. ^ Popular phylogenetic reconstruction methods, such as distance-based methods, attempt to find an optimal tree topology (that reflects the relationships among related sequences and their evolutionary history) by searching through the topology space. Various compromises between the fast (but incomplete) and exhaustive (but computationally prohibitive) search heuristics have been suggested. An intelligent compromise algorithm that relies on a flexible “beam” search principle from the Artificial Intelligence domain and uses the pre-computed local topology reliability information to adjust the beam search space continuously is described in the second chapter of this dissertation. ^ However, sometimes even a (virtually) complete distance-based method is inferior to the significantly more elaborate (and computationally expensive) maximum likelihood (ML) method. In fact, depending on the nature of the sequence data in question either method might prove to be superior. Therefore, it is difficult (even for an expert) to tell a priori which phylogenetic reconstruction method—distance-based, ML or maybe maximum parsimony (MP)—should be chosen for any particular data set. ^ A number of factors, often hidden, influence the performance of a method. For example, it is generally understood that for a phylogenetically “difficult” data set more sophisticated methods (e.g., ML) tend to be more effective and thus should be chosen. However, it is the interplay of many factors that one needs to consider in order to avoid choosing an inferior method (potentially a costly mistake, both in terms of computational expenses and in terms of reconstruction accuracy.) ^ Chapter III of this dissertation details a phylogenetic reconstruction expert system that selects a superior proper method automatically. It uses a classifier (a Decision Tree-inducing algorithm) to map a new data set to the proper phylogenetic reconstruction method. ^

Computer programs for safety analysis.

Federal Highway Administration, Office of Implementation, Washington, D.C.

Environmental scan report on artificial intelligence : strategy considerations for the U.S. Department of the Treasury.

"December 1983."

Computer programs for safety analysis: HISAM users manual and operators guide.

Federal Highway Administration, Washington, D.C.

Computer programs for safety analysis: HISAFE users manual and operators guide.

Federal Highway Administration, Office of Research and Development, McLean, Va.

Products from two computer programs which process digital bathymetric data /

"October 1981."

Report from Task Force on Hydrologic Computer Programs.

Mode of access: Internet.

Documentation of computer programs and automated data systems : proceedings of a symposium held at the National Bureau of Standards, Gaithersburg, MD, October 12, 1976 /

Mode of access: Internet.

Osiris III; an integrated collection of computer programs for the management and analysis of social science data.

v. 1. System and program description.--v. 2. Error Messages.--v. 3. Summary of control cards.--v. 4. Sample jobs.--v. 5. Formulas and statistical references.--v. 6. Primer.

Computer programs for assessing required mission sizes and damage to ground targets in tactical air current operations planning.

"Prepared under Contract AF 19(628)-4805 by the Cornell Aeronautical Laboratory, Inc., of Cornell University."

Computer programs used to analyze wind and bridge data acquired at Sitka, Alaska /

Mode of access: Internet.

An association scheme for artificial intelligence.

Cover title.