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PubMed2006

From machine and tape to structure and function: formulation of a reflexively computing system.

The relationship between structure and function is explored via a system of labeled directed graph structures upon which a single elementary read/write rule is applied locally. Boundaries between static (information-carrying) and active (information-processing) objects, imposed by mandate of the rules or physics in earlier models, emerge instead as a result of a structure-function dynamic that is reflexive: objects may operate directly on their own structure. A representation of an arbitrary Turing machine is reproduced in terms of structural constraints by means of a simple mapping from tape squares and machine states to a uniform medium of nodes and links, establishing computation universality. Exploiting flexibility of the formulation, examples of other unconventional "self-computing" structures are demonstrated. A straightforward representation of a kinematic machine system based on the model devised by Laing is also reproduced in detail. Implications of the findings are discussed in terms of their relation to other formal models of computation and construction. It is argued that reflexivity of the structure-function relationship is a critical informational dynamic in biochemical systems, overlooked in previous models but well captured by the proposed formulation.

Artificial Intelligence↗
PubMedDate not supplied

NCTR computer systems designed for toxicologic experimentation. IV. Experiment information system.

The Experiment Information System (EIS) is a computerized data collection, maintenance, and reporting system for specified information values collected during the lifespan of animals assigned to toxicologic investigations at NCTR. The system records and/or controls experimental variables, which might ultimately affect the results, through the operation and integration of the Diet Preparation Subsystem (DPS), the Environmental Monitoring Subsystem (EMS), the Microbiology Subsystem (MBS), and the Chemistry Data Subsystem (CDS). The fifth component of the EIS, the Experimental Data Collection Subsystem (EDCS), is responsible for handling all data generated by, or attributed to, the animals from assignment until death or removal. Through integration of these five subsystems, the history of an animal while on study is recorded and stored for later recall. In addition, "routine" and "special" reports are made available through the system software which enables stringent control of the experiment by the Principal Investigator, Animal Husbandry, and NCTR Management.

Animals↗
PubMed1993

Diagnosis of selected pulpal pathoses using an expert computer system.

The diagnosis of dental pain that results from a pulpal pathosis may prove to be a confusing and complex issue for both dental students and experienced clinicians alike. A computerized diagnostic expert system, COMENDEX, was developed to aid in the clinical diagnosis of pulpal pathosis and to provide a rapid, accurate second opinion when a human consultant is not readily available. The vast majority of diagnostic expert systems use a single reasoning methodology as their inference mechanism. COMENDEX is a prototype hybrid expert system that combines and exploits the best aspects of both rule-based and statistical reasoning methodologies. The COMENDEX endodontic diagnostic system was tested to determine the validity and accuracy of its diagnoses by the use of a variant of Turing's test and weighted kappa statistic. The promising result obtained from the initial tests suggests that an expert system using this type of hybrid reasoning methodology is well suited to the area of endodontic diagnosis and may prove highly successful if expanded to include other problem areas in oral diagnosis.

Bayes Theorem↗
PubMed1996

[Automatic report documentation in cardiology using a speech recognition system].

Computer systems that can convert spoken text into written text have recently become available. In one such system, the phonetics of spoken words are compared with those of 32 000 stored words, with a statistical program helping to choose the word with the highest probability of being correct. We evaluated the practicability of the IBM Voice Type system for writing medical reports using a cardiologic vocabulary. A total of 200 medical documents were generated with a mean of 301 +/- 52 words. In the mean, 12 +/- 5 words were falsely recognized in each document, resulting in a rate of correct recognition of 95.1 +/- 2.5%. It is possible to correct a falsely recognized word by choosing an alternative word from a provided list, which worked in our case in 51% (6.1 +/- 2.8 words in each document). Correction of falsely recognized words had to be done by manual input 49% of the time (5.9 +/- 2.9 words in each document). The mean time demand for word correction amounted to 57 +/- 15 s for each document, whereas correction by manual input needed more time (37 +/- 14 s) than choosing from a list of alternative words (20 +/- 4s). A requirement for use of the Voice Type system is a reduced speech rate. Dictation of our documents took on average 260 s when done with a normal speech rate, and 400 s when done at a reduced speech rate. In conclusion, automatic writing of cardiologic reports can be done easily and with a low failure rate using the IBM Voice Type system with a cardiologic vocabulary. It takes about 3 min longer to create a medical text 1 1/2 pages long which is free of mistakes by using the Voice Type system than to simply dictate the text. Time can be saved by eliminating the need to check a preliminary report. The major advantage of automated reporting is that the written report is immediately available. For each discipline, specific vocabularies should be validated.

Cardiology↗