The Effect of Temperature on Refining

The results of this work indicate that elevated beating temperature drastically increases beating time and produces detrimental effects on the physical characteristics of the formed sheet as evaluated by wet web strength, tear and tensile. It is thus indicative of the value of cold temperature refining

The NOMAD system : expectation-based detection and correction of errors during understanding of syntactically and semantically ill-formed text

Most large text-understanding systems have been designed under the assumption that the input text will be in reasonably "neat" form (for example, newspaper stories and other edited texts). However, a great deal of natural language text (for example, memos, messages, rough drafts, conversation transcripts, etc.) have features that differ significantly from "neat" texts, posing special problems for readers, such as misspelled words, missing words, poor syntactic construction, unclear or ambiguous interpretation, missing crucial punctuation, etc. Our solution to these problems is to make use of expectations, based both on knowledge of surface English and on world knowledge of the situation being described. These syntactic and semantic expectations can be used to figure out unknown words from context, constrain the possible word senses of words with multiple meanings (ambiguity), fill in missing words (ellipsis), and resolve referents (anaphora). This method of using expectations to aid the understanding of "scruffy" texts has bee incorporated into a working computer program called NOMAD, which understands scruffy texts in the domain of Navy ship-to-shore messages

Elements of latent learning in a maze environment

A general purpose learning program is described which demonstrates a latent learning ability by operating at two separate goal pursuit levels. At one level are the constant, implicit goals associated with the system's memory management mechanisms. At the higher level are the dynamic, explicit behavioral goals which the implicit goals enable by manipulating memory representations to conform to the external surroundings. The program is shown to negotiate a simulated maze environment by the step-wise refinement of its latently learned experiences

Perseverers, recencies and deferrers : new experimental evidence for multiple inference strategies in understanding

In the course of understanding a text, a succession of decision points arise at which readers are faced with the task of choosing among alternative possible interpretations ofthattext. We present new experimental evidence that different readers use different inference strategies to guide their inference behavior during understanding. The choices available to an understander range from various alternative inferential paths to the option of making no inference at a particular point, leaving a 'loose end'. Different inference strategies result in observably different behaviors during understanding, including consistent differences in reading times, and different interpretations of a text. The preliminary experimental results given here so far consistently support a previously published set of hypotheses about the inference process that we have called Judgmental Inference theory

Learning and memory in machines and animals : an AI model that accounts for some neurobiological data

The CEL model of learning and memory (Components of Episodic Learning) [Granger 1982, 1983a, 1983b] provides a process model of certain aspects of learning and memory in animals and humans. The model consists of a set of asynchronous and semi-independent functional operators that collectively create and modify memory traces as a result of experience. The model conforms to relevant results in the learning literature of psychology and neurobiology. There are two goals to this work: one is to create a set of working learning systems that will improve their performance on the basis of experience, and the other is to compare these systems' performance with that of living systems, as a step towards the eventual comparative characterizations of different learning systems.Parts of the model have been implemented in the CEL-0 program, which operates in a 'Maze-World' simulated maze environment. The program exhibits simple exploratory behavior that leads to the acquisition of predictive and discriminatory schemata. A number of interesting theoretical predictions have arisen in part from observation of the operation of the program, some of which are currently being tested in neurobiological experiments. In particular, some neurobiological evidence for the existence of multiple, seperable memory systems in humans and animals is interpreted in terms of the model, and some new experiments are suggested arising from the model's predictions

Parsing with parallelism : a spreading-activation model of inference processing during text understanding

The past decade of reseatch in Natural Language Processing has universally recognized that, since natural language input is almost always ambiguous with respect to its pragmatic implications, its syntactic parse, and even its lexical analysis (i.e., choice of correct word-sense for an ambiguous word), processing natural language input requires decisions about word meanings, syntactic structure, and pragmatic inferences. The lexical, syntactic, and pragmatic levels of inferencing are not as disparate as they have often been treated in both psychological and artificial intelligence research. In fact, these three levels of analysis interact to form a joint interpretation of text.ATLAST (A Three-level Language Analysis SysTem) is an implemented integration of human language understanding at the lexical, the syntactic, and the pragmatic levels. For psychological validity, ATLAST is based on results of experiments with human subjects. The ATLAST model uses a new architecture which was developed to incorporate three features: spreading activation memory, two-stage syntax, and parallel processing of syntax and semantics. It is also a new framework within which to interpret and tackle unsolved problems through implementation and experimentation

STRATEGIST : a program that models strategy-driven and content-driven inference behavior

In the course of understanding a text, different readers use different inference strategies to guide their choice of interpretations of the events in the text. This is in contrast to previous computer models of understanding, which all use the content-driven inference. The separate strategies are theorized to be composed of the same component inference processes, but of different rules for application of the processes. The use of different strategies occasionally results in different results of new experimental data and a working computer program, called STRATEGIST, that models both strategy-drive and content-driven inference behavior. The rules which make up two of these strategies are presented

Scruffy text understanding: design and implementation of tolerant understanders

Most large text-understanding systems have been designed under the assumption that the input text will be in reasonably "neat" form,e.g., newspaper stories and other prepared texts, which typically consist of well-formed sentences and a logical order of presentation of concepts. However, many everyday uses of natural text (e.g., business memos, phone messages, notes) are very ill-informed, containing misspelled words, ungrammatical or only partially complete sentences, and poorly organized ideas.Many large organizations employ humans whose sole job it is to take ill-formed messages and encode them into machine-readable form to be entered into a database. In such cases, there would be great potential benefit if that encoding process could be partially automated. This requires a "scruffy text understander"; i.e., a system that has the ability to correctly analyze the content of such texts in spite of their scruffiness.This paper describes the design and implementation of the NOMAD system, which partially automates the encoding of poorly written Navy messages into well-formed formats. A number of problems are described which arise in the scruffy text domain that have not been dealt with in previous text-understanding systems