The purpose of this paper is to study the basic theoretic structure of intelligent data base by means of logic. There are three parts of this paper. The first part introduces the concept and relational algebra in relational data base. The second part focuses on the relationship between logic and the structure of intelligent data base and compares the intelligent database application. The last part, a SQL (Structure Query Language) queries simulation program using logic programming language Prolog, demonstrates how logic applies to query languages. / Department of Computer Science

A large-scale experimental, state of the art storage facility was constructed on the Macdonald Campus of McGill University. This storage facility will serve as a tool to further investigate many of the laboratory experiments performed in agricultural and food science topics, by providing a representation of actual storage facilities in use in the industry today. The storage facility was fully instrumented to provide valuable data of the stored commodity and it's environment. A custom control software was developed with a user friendly graphical interface. This fully automated software allows data acquisition and control of temperature and relative humidity of the experimental storage facility. / Experiments were performed and the control software provided an adequate temperature and relative humidity control. The controller was based on a conventional PID or proportional, integral and derivative controller. To further improve the control of the storage facility, a novel multivariable PID controller was developed using enthalpy as the process variable, which encompasses both temperature and relative humidity. The novel controller was tested using a mathematical model developed. Simulations were performed comparing the performance of the novel multivariable controller to two other conventional controllers. The results demonstrate that the novel multivariable PID controller is capable of controlling temperature and relative humidity better than the other two conventional control techniques.

In this dissertation we have addressed the problem of modeling expertise in domains characterized by unquantifiable, often subjective, information, and using that model of expertise as the foundation for building computer-based decision support systems. The key feature of the expert model is to make explicit the essential characteristics of the knowledge experts use to process objective, quantitative information, for making decisions in environments rich in qualitative data. This model is then used as the basis for an "intelligent" interactive assistant that presents information appropriate for the context to operators who may not have developed the necessary expertise. The core of the assistant is a heuristic algorithm that reflects what an expert decision maker would actually do. The algorithm incorporates a set of production rules, i.e., if-then-else rules, to define relevance conditions of quantitative data. These rules employ a dominance principle, i.e., a heuristic association of the relevance of quantitative data with the attributes of qualitative data, characterized as a set of ordered values. The heuristic algorithm is embedded in the assistant and is used to assist non-expert operators in locating information useful for making decisions. The modeling methodology and the heuristic algorithm are applicable for modeling expertise in a class of decision problems characterized by large amounts of qualitative and quantitative data. The process of structuring the expert's knowledge requires empirical evidence from actual decision problems; this evidence feeds the algorithm with heuristic associations between qualitative and quantitative data. The algorithm uses the dominance principle to decide what information to present for a particular set of conditions.

Thesis (Ph. D.)--State University of New York at Binghamton, Thomas J. Watson School of Engineering and Applied Science, Department of Systems Science and Industrial Engineering, 2008. / Includes bibliographical references.

Thesis (Ph. D.)--Computing, Georgia Institute of Technology, 2008. / Committee Member: Ahamad, Mustaque; Committee Member: Eisenhauer, Greg; Committee Member: Milojicic, Dejan; Committee Member: Pu, Calton; Committee Member: Schwan, Karsten.

Thesis (M.S.)--Kutztown University of Pennsylvania, 1991. / Source: Masters Abstracts International, Volume: 45-06, page: 3181. Typescript. Includes bibliographical references (leaves 75-76).

Thesis (Ph. D.)--University of Missouri-Columbia, 1997. / Typescript. Vita. Includes bibliographical references (leaves [179]-199). Also available on the Internet.

Thesis (Ph. D.)--University of Missouri-Columbia, 1997. / Typescript. Vita. Includes bibliographical references (leaves [179]-199). Also available on the Internet.

Thesis (Ph.D.)--Computing, Georgia Institute of Technology, 2009. / Committee Chair: Aaron Bobick; Committee Member: Charles Isbell; Committee Member: David Hogg; Committee Member: Irfan Essa; Committee Member: James Rehg

Dissertation (PhD)--University of Stellenbosch, 2008. / Bibliography. Also available via the Internet.