"Revision of the author's thesis, University of California, Berkeley, 1979." / Includes bibliographical references (p. [273]-281) and index.

Thesis (M.S. in Information Technology Management)--Naval Postgraduate School, June 2003. / Thesis advisor(s): Daniel R. Dolk, Glenn Cook. Includes bibliographical references (p. 113-114). Also available online.

Thesis (Ph. D. (Educational Management and Policy Studies))--University of Pretoria, 2001. / Includes bibliographical references.

Includes bibliographical references (p. 147-159).

Thesis (M. Phil.)--Hong Kong University of Science and Technology, 2003. / Includes bibliographical references (leaves 51-52). Also available in electronic version. Access restricted to campus users.

Artificial Intelligence Lab, Department of MIS, University of Arizona / Information science researchers have recently turned to new artificial intelligence-based inductive learning techniques including neural networks, symbolic learning and genetic algorithms. An overview of the new techniques and their usage in information science research is provided. The algorithms adopted for a hybrid genetic algorithms and neural nets based system, called GANNET, are presented. GANNET performed concept (keyword) optimization for user-selected documents during information retrieval using the genetic algorithms. It then used the optimized concepts to perform concept exploration in a large network of related concepts through the Hopfield net parallel relaxation procedure. Based on a test collection of about 3,000 articles from DIALOG and an automatically created thesaurus, and using Jaccard's score as a performance measure, the experiment showed that GANNET improved the Jaccard's scores by about 50% and helped identify the underlying concepts that best describe the user-selected documents.

Artificial Intelligence Lab, Department of MIS, University of Arizona / Crime and police report information is rapidly migrating from paper records to automated records management databases. Most mid and large sized police agencies have such systems that provide access to information by their own personnel, but lack any efficient manner by which to provide that information to other agencies. Criminals show no regard for jurisdictional boundaries and in fact take advantage of the lack of communication across jurisdictions. Federal standards initiatives such as the National Incident Based Reporting System (NIBRS, US Department of Justice 1998), are attempting to provide reporting standards to police agencies to facilitate future reporting and information sharing among agencies as these electronic reporting systems become more widespread. We integrated platform-independence, stability, scalability, and an intuitive graphical user interface to develop the COPLINK system, which is currently being deployed at Tucson Police Department (TPD). User evaluations of the application allowed us to study the impact of COPLINK on law enforcement personnel as well as to identify requirements for improving the system and extending the project. We are currently in the process of extending the functionality of COPLINK in several areas. These include textual analysis, collaboration, visualization and geo-mapping.

A database schema should consist of structures and semantic integrity constraints. Se mantic integrity constraints (SICs) are invariant restrictions on the static states of the stored data and the state transitions caused by the primitive operations: insertion, dele tion, or update. Traditionally, database design has been carried out on an ad hoc basis and focuses on structure and efficiency. Although the E-R model is the popular concep tual modelling tool, it contains few inherent SICs. Also, although the relational database model is the popular logical data model, a relational database in fourth or fifth normal form may still represent little of the data semantics. Most integrity checking is distributed to the application programs or transactions. This approach to enforcing integrity via the application software causes a number of problems. Recently, a number of systems have been developed for assisting the database design process. However, only a few of those systems try to help a database designer incorporate SICs in a database schema. Furthermore, current SIC representation languages in the literature cannot be used to represent precisely the necessary features for specifying declarative and operational semantics of a SIC, and no modelling tool is available to incorporate SICs. This research solves the above problems by presenting two models and one subsystem. The E-R-SIC model is a comprehensive modelling tool for helping a database designer in corporate SICs in a database schema. It is application domain-independent and suitable for implementation as part of an automated database design system. The SIC Repre sentation model is used to represent precisely these SICs. The SIC elicitation subsystem would verify these general SICs to a certain extent, decompose them into sub-SICs if necessary, and transform them into corresponding ones in the relational model. A database designer using these two modelling tools can describe more data semantics than with the widely used relational model. The proposed SIC elicitation subsystem can provide more modelling assistance for him (her) than current automated database design systems.

No description available.

Uncertainty has a large effect on projects in the oil and gas industry, because most aspects of project evaluation rely on estimates. Industry routinely underestimates uncertainty, often significantly. The tendency to underestimate uncertainty is nearly universal. The cost associated with underestimating uncertainty, or overconfidence, can be substantial. Studies have shown that moderate overconfidence and optimism can result in expected portfolio disappointment of more than 30%. It has been shown that uncertainty can be assessed more reliably through look-backs and calibration, i.e., comparing actual results to probabilistic predictions over time. While many recognize the importance of look-backs, calibration is seldom practiced in industry. I believe a primary reason for this is lack of systematic processes and software for calibration. The primary development of my research is a database application that provides a way to track probabilistic estimates and their reliability over time. The Brier score and its components, mainly calibration, are used for evaluating reliability. The system is general in the types of estimates and forecasts that it can monitor, including production, reserves, time, costs, and even quarterly earnings. Forecasts may be assessed visually, using calibration charts, and quantitatively, using the Brier score. The calibration information can be used to modify probabilistic estimation and forecasting processes as needed to be more reliable. Historical data may be used to externally adjust future forecasts so they are better calibrated. Three experiments with historical data sets of predicted vs. actual quantities, e.g., drilling costs and reserves, are presented and demonstrate that external adjustment of probabilistic forecasts improve future estimates. Consistent application of this approach and database application over time should improve probabilistic forecasts, resulting in improved company and industry performance.