Knowledge identification phase of natural language analysis

Case organization of verbs has provided a powerful mechanism for natural language analysis systems. However, only simple semantic-marker-like information has been used to determine the acceptibility of lexical elements as case-role fillers. Actually, this ability is influenced by more intricate relations among words. In addition, a case-based view of semantic knowledge often leads to the separate specification of each shade of meaning of a verb. These two problems are addressed in this thesis. A case-like organization of semantic knowledge which includes a network of relations among lexical elements is presented. Any piece of information contained in the system may be used as a case-frame specification, or it could be used as information which determines case-role fulfillment. Rules for the use of this information have been designed to permit a single case-frame to recognize many shades of meaning of a verb, even to the point of accepting metaphoric language use, The network of relations is hierarchically organized, and knowledge is retained at many levels of generalization. Along with the existence of case-organization in the network, these multiple levels provide some control over the traversal of the network. A small implementation is provided to demonstrate the use of a variety of strategies for fitting case-frames to input. The model is intended as a bottom-up component for the identification of those pieces of information which may be relevant to a given input.Science, Faculty ofComputer Science, Department ofGraduat

Knowledge-based visual interpretation using declarative schemata

One of the main objectives of computer vision systems is to produce structural descriptions of the scenes depicted in images. Knowledge of the class of objects being imaged can facilitate this objective by providing models to guide interpretation, and by furnishing a basis for the structural descriptions. This document describes research into techniques for the representation and use of knowledge of object classes, carried out within the context of a computational vision system which interprets line drawings of human-like body forms. A declarative schemata format has been devised which represents structures of image features which constitute depictions of body parts. The system encodes relations between these image constructions and an underlying three dimensional model of the human body. Using the component hierarchy as a structural basis, two layers of representation are developed. One references the fine resolution features, and the other references the coarse resolution. These layers are connected with links representative of the specialization/generalization hierarchy. The problem domain description is declarative, and makes no commitment to the nature of the subsequent interpretation processes. As a means of testing the adequacy of the representation, portions have been converted into a PROLOG formulation and used to "prove" body parts in a data base of assertions about, image properties. The interpretation phase relies on a cue/model approach, using an extensive cue table which is automatically generated from the problem domain description. The primary mechanisms for control of interpretation possibilities are fashioned after network consistency methods. The operation of these mechanisms is localized and separated between operations at the feature level and at the model level. The body drawing interpretation system is consistent with aspects of human visual perception. The system is capable of intelligent selection of processing locations on the basis of the progress of interpretation. A dual resolution retina is moved about the image collecting fine level features in a small foveal area and coarse level features in a wider peripheral area. Separate interpretations are developed locally on the basis of the two different resolution levels, and the relation between these two interpretations is analyzed by the system to determine locations of potentially useful information.Science, Faculty ofComputer Science, Department ofGraduat

Evidence that S-adenosyl-L-methionine diastereoisomers may reduce ischaemia-reperfusion injury by interacting with purinoceptors in isolated rat liver

1. Mechanisms underlying the haemodynamic activity of diastereoisomers of S-adenosyl-L-methionine (SAM) were investigated using inhibitors of purinoceptors and nitric oxide (NO) synthase in perfused rat livers damaged by sequential 24 h cold and 20 min rewarming ischaemia+reperfusion. 2. Stored livers were flushed with 10 ml saline alone (control) or with added (R,S) or (S,S) SAM (100 μM) and reperfused in the absence (control) or presence of 10 μM 8-phenyltheophylline (8-PT) or 100 μM L-N-monomethylarginine (L-NMMA). 3. Both SAM diastereoisomers rapidly increased blood flow and bile production versus controls (P<0.001) but the (R,S) isomer induced greater increases in blood flow and the (S,S) isomer greater increases in bile production: 625 versus 596 versus 518 ml blood flow and 100 versus 119 versus 56 mg bile production per g liver over 3 h in (R,S), (S,S) and control, respectively. 4. 8-PT prevented the enhancement of blood flow by (S,S) SAM (529 versus 596 ml g (−1)liver over 3 h for (S,S) SAM alone, P<0.001), but was without effect in control livers. 8-PT also reduced SAM-enhanced bile production: 51 versus 119 mg g (−1)liver over 3 h, P<0.001. L-NMMA reduced blood flow and bile production similarly in the absence or presence of (S,S) SAM. 5. Thus, SAM may improve liver perfusion after ischaemia-reperfusion injury via stimulation of P(1) (A(2)) purinoceptors at which SAM shows activity. The choleretic activity of (S,S) SAM is disproportionately greater than enhanced blood flow and may occur independently of a NO-dependent component of bile production