A Study of Qualitative and Geometric Knowledge in Reasoning about Motion

Reasoning about motion is an important part of our commonsense knowledge, involving fluent spatial reasoning. This work studies the qualitative and geometric knowledge required to reason in a world that consists of balls moving through space constrained by collisions with surfaces, including dissipative forces and multiple moving objects. An analog geometry representation serves the program as a diagram, allowing many spatial questions to be answered by numeric calculation. It also provides the foundation for the construction and use of place vocabulary, the symbolic descriptions of space required to do qualitative reasoning about motion in the domain. The actual motion of a ball is described as a network consisting of descriptions of qualitatively distinct types of motion. Implementing the elements of these networks in a constraint language allows the same elements to be used for both analysis and simulation of motion. A qualitative description of the actual motion is also used to check the consistency of assumptions about motion. A process of qualitative simulation is used to describe the kinds of motion possible from some state. The ambiguity inherent in such a description can be reduced by assumptions about physical properties of the ball or assumptions about its motion. Each assumption directly rules out some kinds of motion, but other knowledge is required to determine the indirect consequences of making these assumptions. Some of this knowledge is domain dependent and relies heavily on spatial descriptions.

Qualitative Analysis of MOS Circuits

With the push towards sub-micron technology, transistor models have become increasingly complex. The number of components in integrated circuits has forced designer's efforts and skills towards higher levels of design. This has created a gap between design expertise and the performance demands increasingly imposed by the technology. To alleviate this problem, software tools must be developed that provide the designer with expert advice on circuit performance and design. This requires a theory that links the intuitions of an expert circuit analyst with the corresponding principles of formal theory (i.e. algebra, calculus, feedback analysis, network theory, and electrodynamics), and that makes each underlying assumption explicit.

Qualitative Process Theory

Objects move, collide, flow, bend, heat up, cool down, stretch, compress and boil. These and other things that cause changes in objects over time are intuitively characterized as processes. To understand common sense physical reasoning and make programs that interact with the physical world as well as people do we must understand qualitative reasoning about processes, when they will occur, their effects, and when they will stop. Qualitative Process theory defines a simple notion of physical process that appears useful as a language in which to write dynamical theories. Reasoning about processes also motivates a new qualitative representation for quantity in terms of inequalities, called quantity space. This report describes the basic concepts of Qualitative Process theory, several different kinds of reasoning that can be performed with them, and discusses its impact on other issues in common sense reasoning about the physical world, such as causal reasoning and measurement interpretation. Several extended examples illustrate the utility of the theory, including figuring out that a boiler can blow up, that an oscillator with friction will eventually stop, and how to say that you can pull with a string but not push with it. This report also describes GIZMO, an implemented computer program which uses Qualitative Process theory to make predictions and interpret simple measurements. The represnetations and algorithms used in GIZMO are described in detail, and illustrated using several examples.

Qualitative and Quantitative Knowledge in Classical Mechanics

This thesis investigates what knowledge is necessary to solve mechanics problems. A program NEWTON is described which understands and solves problems in mechanics mini-world of objects moving on surfaces. Facts and equations such as those given in mechanics text need to be represented. However, this is far from sufficient to solve problems. Human problem solvers rely on "common sense" and "qualitative" knowledge which the physics text tacitly assumes to be present. A mechanics problem solver must embody such knowledge. Quantitative knowledge given by equations and more qualitative common sense knowledge are the major research points exposited in this thesis. The major issue in solving problems is planning. Planning involves tentatively outlining a possible path to the solution without actually solving the problem. Such a plan needs to be constructed and debugged in the process of solving the problem. Envisionment, or qualitative simulation of the event, plays a central role in this planning process.

Qualitative Knowledge, Casual Reasoning and the Localization of Failures

This report investigates some techinques appropriate to representing the knowledge necessary for understanding a class of electronic machines -- radio receivers. A computational performance model - WATSON - is presented. WATSONs task is to isolate failures in radio receivers whose principles of operation have been appropriately described in his knowledge base. The thesis of the report is that hierarchically organized representational structures are essential to the understanding of complex mechanisms. Such structures lead not only to descriptions of machine operation at many levels of detail, but also offer a powerful means of organizing "specialist" knowledge for the repair of machines when they are broken.

Quantitative and qualitative analysis of flavonoids in leaves of Adinandra nitida by high performance liquid chromatography with UV and electrospray ionization tandem mass spectrometry detection

The extract of Adinandra nitida leaves, named as Shiyacha in China, was studied by high performance liquid chromatography (HPLC)-ultraviolet detection-electrospray ionisation (ESI) tandem mass spectrometry (MS). Under the optimized condition, the analysis could be finished in 45 min on a Hypersil C18 column combined with negative ion detection using information-dependent acquisition (IDA) mode of a Q TRAP (TM) instrument. Six flavonoids were identified as epicatechin, rhoifolin, apigenin, quercitrin, camellianin A, and camellianin B among which rhoifolin was for the first time found in Shiyacha. And the fragment pathways of these flavonoids were elucidated. Furthermore, with epicatechin, rhoifolin, and apigenin as markers, the quality control method for Shiyacha and its relevant product was firstly established. Calibration linearity was good (R-2 > 0.9992) over a three to four orders of magnitude concentration range with an S/N = 3 detection limit of 2.5 ng. (c) 2004 Elsevier B.V. All rights reserved.

Ambiguities and Deviations in Qualitative Circuit Analysis

Lee M.H., Bell J. and Coghill G.M., Ambiguities and Deviations in Qualitative Circuit Analysis, in Proc. QR?2001, 15th Int. Workshop on Qualitative Reasoning, San Antonio, Texas, May 2001, pp51-58.

Many-Valued Logic and Qualitative Modelling of Electrical Circuits

Lee M.H., Many-Valued Logic and Qualitative Modelling of Electrical Circuits, in Proc. QR?2000, 14th Int. Workshop on Qualitative Reasoning, Morelia, Mexico June 3rd - 7th 2000.

Qualitative Modelling of Linear Networks in Engineering Applications

Lee M.H., Qualitative Modelling of Linear Networks in Engineering Applications, in Proc. ECAI?2000, 14th European Conf. on Artificial Intelligence, Berlin, August 19th - 25th 2000, pp161-5.

Qualitative Modelling of Linear Networks in ECAD Applications

Lee M.H., Qualitative Modelling of Linear Networks in ECAD Applications, Expert Update, Vol. 3, Num. 2, pp23-32, BCS SGES, Summer 2000. Qualitative modeling of linear networks in ecad applications (1999) by M Lee Venue: Pages 146?152 of: Proceedings 13th international workshop on qualitative reasoning, QR ?99

Qualitative modelling of unknown interface behaviour

M. H. Lee, and S. M. Garrett, Qualitative modelling of unknown interface behaviour, International Journal of Human Computer Studies, Vol. 53, No. 4, pp. 493-515, 2000

Qualitative Circuit Models in Failure Analysis Reasoning

Lee M.H., Qualitative Circuit Models in Failure Analysis Reasoning, AI Journal. vol 111, pp239-276.1999.

Qualitative Modelling of Linear Networks in ECAD Applications

Lee M.H., Qualitative Modelling of Linear Networks in ECAD Applications, Proc. 13th Int. Workshop on Qualitative Reasoning, (QR'99), Loch Awe, Scotland, 1999, pp146-52.

On the use of qualitative reasoning to simulate and identify metabolic pathways

King, R.D., Garrett, S.M., Coghill, G.M. (2005). On the use of qualitative reasoning to simulate and identify metabolic pathways. Bioinformatics 21(9):2017-2026 RAE2008

Learning Qualitative Metabolic Models

Coghill, G. M., Garrett, S. M. and King, R. D. (2004) Learning Qualitative Metabolic Models. European Conference on Artificial Intelligence (ECAI'04)