Abstract: A system for processing Aeromagnetic survey data to determine depth to basement rock is disclosed. The system uses Neural Networks having an input layer of elements, a hidden layer of elements and an output layer of elements which are interconnected by a weighted system of interconnections. A training session using known input and output data is used to train the Neural Network by adjusting the weighting functions repetitively to minimize any error in the output of the Neural Network.

Abstract: A method and apparatus to reduce conditional statements in normal code flow. A plurality of contiguous memory pages are allocated as either protected or unprotected. A pointer is defined to point to an address such that an operation (write or read) to an address in the unprotected page will occur when the conditional value is within an accepted range. The address is calculated by using a function of the conditional value as an offset to the pointer. When the conditional value enters the non-accepted or error range, the operation to the address of the pointer offset by the function of conditional value will fall within the allocated protected page. This will result in a faulting pointer and invocation of a signal handler which is independent of the normal code and only executed responsive to the conditional value entering an error range.

Abstract: A system for knowledge representation in a computer, together with the ability to recognize, store and use patterns in the knowledge representation, together with the ability for Natural Language Interaction with the knowledge representation system, together with means to automatically transform information in the knowledge representation into a multitude of documents or other human interpretable displays in a plurality of different formats or views. User interaction with the knowledge representation through the view documents is achievable through a multitude of various possible formats. The Knowledge Representation system defines a novel database engine constituting a method for modeling knowledge as a network of concepts and a plurality of relationships between the concepts comprising the network. Each concept is represented as a record in the database which is identified by a unique record reference number.

Abstract: An improved expert system is disclosed wherein rules are organized into domains and subdomains, and objects are passed to rules to be operated upon. Prior to operating upon any object, the domain determines if the object is of the type which is to be operated upon by rules within the rule domain. If not, the rules are not applied to the object.

Abstract: A system which performs a plurality of independent analysis procedures simultaneously, possibly involving differing types of tissues and differing process steps, comprising a robotic arm, which moves the different tissue samples among a plurality of processing stations, and a processor, which selects the next tissue sample to move, when to move it, and where to move it to. The processor directs the robotic arm to interleave the differing process steps. The processing stations comprise workstations for performing individual steps of the tissue assay procedures, such as solution trays. The processor selects a tissue sample to be moved in response to timing information about the procedures. While the processor is directing the robotic arm to move, the processor monitors progress information and can alter the sequence of process steps in response to the progress information and information from an operator.

Abstract: A model information control system ("MICS") is used in conjunction with a user-defined information model and one or more conventional information system program modules or "functions"to execute business applications. Following each execution of an action defined by the information model, an Expected Behavior Control System ("EBCS") determines if the resulting behavior is consistent with expected behavior and conforms the behavior to the expected behavior if necessary. The EBCS may also change the behavior of an application processing system or application program by enforcing a new behavior for the application processing system or application program without modifying them. The MICS includes an event-action-state machine that manipulates the user-defined information model and the functions.

Abstract: A computerized learning machine for implementing adaptive problem solving includes an information processing device, a storage device, an output device and an input device. The adaptive problem solving method is implemented by: a) retrieving from the storage device a first question; b) outputting to the output device the first question; c) receiving from the input device an answer from the user; d) assigning a fuzzy logic coefficient to the answer; e) accessing from the storage device a learning route authority to determine the identity of a second question, the determination being dependent on the fuzzy logic coefficient; and f) repeating steps a) to e) for the second question.

Abstract: In a client/server environment, a rule-based system for the provision of complex navigational logic in an application comprises a Navigation Analysis Vehicle ("NAV") and a Matrix Analysis Package ("MAP"). The MAP facilitates creation of navigation rules for linkage with the rest of the application. In a preferred embodiment of the invention, the NAV communicates navigational instructions to a user interface for the display and the take-down of screens and also communicates with other processes such as editors and data manipulators. After the navigation rules are created, those rules are then applied to provide navigational logic for the user interface for the processing the user interface screens. MAP creates the navigation rules in a user-friendly, C-like language and parses them into ANSI-standard C language for linkage with other processes that control the user interface.

Abstract: A method of creating a database for facilitating a synthetic interview begins with the step of generating questions. The questions and responses to the questions are recorded. A transcript of the recorded questions and responses is created. An association between each question and the response thereto is maintained. Each of the responses and each of the questions is expanded with semantic information. Inverted indices are created for the semantic expansions of the responses, the questions, and the transcripts of the responses and questions to enable retrieval of the recorded responses in a seamless manner. A method is also disclosed for creating a database for creating a synthetic interview from existing material.

Abstract: An apparatus for simulating the behavior of a biological neuron. In accordance with one aspect of the invention, a charge-carrying component is fabricated from semiconductor material and is disposed above a semiconductor substrate. The charge-carrying component is separated from the substrate, and substantially surrounded, by an isolating material, such as an oxide (e.g., silicon dioxide). Advantageously, the substantial isolation of the component helps ensure the preservation of electrical charge on the charge-carrying component. Indeed, in accordance with a preferred embodiment, virtually no charge leakage occurs, and absent purposeful charge injection or drainage (described below), the charge deposited on the charge carrying component will be preserved for a very long time.

Abstract: A method and apparatus for selecting terms, preferably higher order terms, for use in a stimulus vector of a holographic neural network. The method includes an evolutionary type algorithm in which stimulus vector arrangements are preferably modelled as chromosomes containing genes that each uniquely identify one of a plurality of terms in a corresponding stimulus vector. Techniques for introducing variation and for selecting fit chromosome/stimulus vector arrangements are also disclosed, as is an apparatus for executing the term selecting method.

Abstract: An apparatus uses a computer-controlled algorithm that enables production of high-quality layouts and charge maps or, set-ups for arbitrary printed circuit boards for electronic component placement machines alone or as one of many in a production line. A class of algorithms known as genetic algorithms employing an initial population of chromosomes are used. Each chromosome represents a set of parameters that control how a layout and charge maps are generated. Problem descriptors, based on one time code are generated. An adaptive searcher searches parameters and generates trial solutions as chromosomes and a heuristic layout generator interprets these chromosomes to generate the layout and charge maps using the problem descriptors.

Abstract: A method is presented for evaluating data to predict the future occurrence of a medical condition that is presently clinically occult or which has not yet occurred. Specifically, the method uses a neural network to analyze and interpret DNA flow cytometric histograms. A first set of DNA histograms taken from tumors from patients having known relapse rates are used to train the neural network, an then the trained network is applied to predict the relapse rates of patients using DNA histograms of tumors from those patients. Prognosis according to this method can be performed using only diploid histograms, using only aneuploid histograms, or using a combination of diploid and aneuploid histograms.

Abstract: A neural network has a plurality of network neurons and a plurality of network connections which connect each network neuron to one or more other network neurons. Each network neuron has control parameters in the form of an associated threshold value and/or signal distribution when a signal is supplied to other network neurons, and supplies a signal to the output in response to a comparison between said threshold value and a signal received on the input. One or more network neurons serve as network inputs, which supply an output representation in dependence on the sensed parameters applied to the network input. The network has associated with it sensor neurons which register changes in the conditions under which the network works, and the control parameters of the network neurons are regulated in dependence on this.

Abstract: Concurrent tradeoff analysis (10) first ascertains a set of constraints (16) and variables (18) for specifying a solution, and then defines characteristics for specifying the merit of the solution. Computations are made to determine the values for the variables (18) and characteristics, which represent a current solution state. The current solution state is checked (42) to ensure that there are no violations of the constraints (16). If a violation exists, one or more alternatives are generated (46) via a number of methods, and the alternatives are evaluated (48) along with the current solution state. One or more most promising alternative is chosen, and the process proceeds until values for all of the variables (18) and characteristics are computed.

Abstract: A method for classifying a test subject in one of a plurality of states in a domain, a domain being a set of facts, a quality measure, or a combination of the two. The set of facts for a knowledge domain is any set of facts while the set of facts for a functionality domain is a set of facts relating to the functionality of a test subject. A state is characterized by a subset of facts, a value for a quality measure, or a combination of a subset of facts and a value for a quality measure.

Abstract: A software agent which performs autonomous learning in a real-world environment, implemented in a case-based reasoning system and coupled to a sensor for gathering information from, and to an effector for manipulating, its environment. A case base which is tuned in response to an evaluation of how well the agent is operating in that environment. A memory of cases, the contents of that memory being determined by a genetic technique, including producing new cases which may never have been encountered in the environment, evaluating cases in response to a history of previous matches and in response to an external stimulus, and selecting a limited set of cases which provides a preferred model of the environment.

Abstract: An improved Genetic Algorithm scheduling system includes system for encoding and testing hard constraint information. Each resource and task includes an associated capability and constraint indicating component. A comparison of the capability and constraint components provides an indication of the associated resource is capable of perform the proposed task. The system also includes a method of creating genomes using cost factors and weight settings to produce initial genomes which encode at least partly optimized schedules. The weight settings can be manipulated to emphasize different cost factors during genomes creation. This method also allows changes to be added into a running GA scheduling system, in that new or changed tasks and new or changed resources are encoded into the genome population.

Abstract: A computer implemented method for defining, organizing, and analyzing systems and the connections, or relationships, between the systems, in a flexible manner according to a user's focus, perspective, and desired level of detail. A set of systems is selected by a user. A set of attributes by which to distinguish the systems is selected by the user. The systems are grouped according to the values for the selected attributes, thereby forming a taxonomy tree. A user then selects one or more resources that are potentially produced by, i.e., flow from, or consumed by, i.e., flow to, one or more of the systems of interest. A hypercube data structure is created that defines between which systems the resources flow. Utilizing the taxonomy tree, the hypercube further summarizes resource flows between parent systems for which resource flows are defined between their corresponding child systems.

Abstract: A first information transforming unit, capable of learning, transforms state information acquired from an object into a first intermediate representation. A second information transforming unit, capable of learning, transforms knowledge information derived, from attributes of the object, by a human being into a second intermediate representation. A fusing unit produces a common intermediate representation using the first intermediate representation and the second intermediate representation. The common intermediate representation is used as a teacher signal in order to train the first and second information transforming units. Thereafter, an intermediate representation made by transforming state information acquired from a certain object will be consistent with an intermediate representation made by transforming knowledge information derived from the object by a human being.