Abstract: An aircraft includes an engine and a system that is configured to detect an event associated with the engine during a take-off. The system is further configured to determine a speed of the aircraft a particular time after the event and to determine a remaining distance between the aircraft and an end of a runway at the particular time. The system is also configured to compare the speed of the aircraft to a take-off rejection speed threshold. The take-off rejection speed threshold indicates a maximum aircraft speed that would result in the aircraft stopping prior to a particular distance from the end of the runway. The take-off rejection speed threshold is selected from a plurality of aircraft speeds generated during aircraft deceleration simulations. The system is also configured to generate an indication recommending whether to continue the take-off based on comparison.

Abstract: A method for identifying a component part includes receiving a digital image of an object and textual information about the object and accessing images of component parts and textual information about the component parts. The method further includes applying the digital image to a first classifier trained on the images of the component parts to classify the object as a first of the component parts and applying the textual information about the object to a second classifier trained on the textual information about the component parts to recognize the textual information as information about the first of the component parts or a second of the component parts. The method further includes identifying the object as a component part that is the first of the component parts or the second of the component parts and accessing a data record with information about the component part.

Abstract: A method for identifying a component part includes receiving a digital image of an object and textual information about the object and accessing images of component parts and textual information about the component parts. The method further includes applying the digital image to a first classifier trained on the images of the component parts to classify the object as a first of the component parts and applying the textual information about the object to a second classifier trained on the textual information about the component parts to recognize the textual information as information about the first of the component parts or a second of the component parts. The method further includes identifying the object as a component part that is the first of the component parts or the second of the component parts and accessing a data record with information about the component part.

Abstract: Provided are improved systems, methods, and computer programs to facilitate predictive accuracy for strategic decision support using a query specific Bayesian network. An unconstrained domain model is defined by domain concepts and causal relationships between the domain concepts. Each causal relationship includes a value for the weight of causal belief for the causal relationship. In response to a query, the unconstrained domain model is transformed into a query specific Bayesian network for the domain model by identifying one or more cycles in the unconstrained domain model, eliminating the one or more cycles from the unconstrained domain model; identifying a sub-graph of the unconstrained domain model that is relevant to a query and creating one or more conditional probability tables that comprise the query specific Bayesian network.

Abstract: An aircraft includes an engine and a system that is configured to detect an event associated with the engine during a take-off. The system is further configured to determine a speed of the aircraft a particular time after the event and to determine a remaining distance between the aircraft and an end of a runway at the particular time. The system is also configured to compare the speed of the aircraft to a take-off rejection speed threshold. The take-off rejection speed threshold indicates a maximum aircraft speed that would result in the aircraft stopping prior to a particular distance from the end of the runway. The take-off rejection speed threshold is selected from a plurality of aircraft speeds generated during aircraft deceleration simulations. The system is also configured to generate an indication recommending whether to continue the take-off based on comparison.

Abstract: According to an embodiment, a computer-implemented method of identifying delay causing product assembly jobs in a factory that produces multiple products includes acquiring delay times for each of a plurality of jobs performed for assembly of each of a plurality of products at the factory, ranking the jobs according to a number of products affected by delay times, whereby a ranked jobs list is produced, adjusting at least one of a delay threshold, a job rank threshold, or a number of products threshold until a plot of amount of products affected by a delay exceeding the delay threshold as a dependent variable, versus ranked jobs of the ranked jobs list as an independent variable, exceeds the number of products threshold at the job rank threshold, and outputting an initial segment of the ranked jobs list up to the job rank threshold.

Abstract: Provided are improved systems, methods, and computer programs to facilitate predictive accuracy for strategic decision support using a query specific Bayesian network. An unconstrained domain model is defined by domain concepts and causal relationships between the domain concepts. Each causal relationship includes a value for the weight of causal belief for the causal relationship. In response to a query, the unconstrained domain model is transformed into a query specific Bayesian network for the domain model by identifying one or more cycles in the unconstrained domain model, eliminating the one or more cycles from the unconstrained domain model; identifying a sub-graph of the unconstrained domain model that is relevant to a query and creating one or more conditional probability tables that comprise the query specific Bayesian network.

Abstract: Systems and methods of recommending replacement of parts on machines. In one embodiment, a method of recommending replacement includes receiving data for a part type, determining a cumulative probability function for an infant mortality of the part type, and determining a cumulative probability function for a natural life of the part type. The method includes defining a lower time boundary and an upper time boundary between which the part type is considered operative. The lower time boundary is defined at a time point at an intersection between the cumulative probability function for the infant mortality and the cumulative probability function for the natural life of the part type. The upper time boundary is defined at a time point representing an estimated end of an operative life of the part type. Recommending replacement of a part on a machine may then be determined based on the upper and lower time boundaries.

Abstract: Devices and methods for use in forecasting the state of one or more of a plurality of variables within a domain are provided. One example method includes determining, at a processor, a first probability curve indicative of a probability of a change-in-state of the first variable over a first interval, the first probability defining a first substantially continuous time trajectory, determining, at the processor, a second probability curve indicative of a probability of a change-instate of the second variable over a second interval, the second probability defining a second substantially continuous time trajectory, the first interval at least partially overlapping with the second interval, and displaying, at a display device, the first and second probability curves substantially in real time, thereby permitting a user to compare the relative probabilities of the change-in-state of at least one of the first and second variables.

Abstract: Provided are improved systems, methods, and computer programs to facilitate predictive accuracy for strategic decision support using Continuous Time Bayesian Networks. A simple semantic is provided for both probabilistic and temporal relationships that can be automatically translated into functioning Bayesian and Continuous Time Bayesian Network formalisms and applied by a user for reasoning analysis, such as to assess a hypothesis or respond to a query with a probabilistic and temporal prediction of a future event.

Abstract: A method, apparatus and computer program product are provided for constructing a diagnostic network model in a more efficient and timely manner and with improved consistency. A structured electronic representation of a document is automatically reviewed to identify the symptoms experienced by the complex system, the plurality of components of the complex system and the causal relationships between a failure of the respective components and the occurrence of the various symptoms. Respective probabilities can be associated with the causal relationships between the symptoms and the failure of the various components. A network model, such as a Bayesian network model, may then be automatically constructed to represent the symptoms, the components, the causal relationships between failure of the components and exhibition of the symptoms, and the probabilities of the respective causal relationships.

Abstract: A computer-based searching method is described that includes receiving, at a computer, a search concept that includes a plurality of principal words, determining a set of semantically similar words for at least one of the principal words, calculating a degree of membership for each word in each set that reflects a semantic similarity in meaning to the principal word of the set, performing the search, computing a score based at least on the degrees of membership for the words in the word set, and sorting the results using the computed scores.

Abstract: Technologies are described herein for detecting and recovering from a fire event within an aircraft. The technologies receive sensor data from a number of sensors associated with an aircraft. A determination is made as to whether the sensor data exceeds predefined thresholds indicating the fire event within the aircraft. In response to determining that the sensor data exceeds the predefined thresholds indicating the fire event, the technologies determine a location of the fire event within the aircraft based on the sensor data and depower components of the aircraft associated with the fire event. The technologies then initiate a fire suppressant mechanism within the aircraft directed to the location of the fire event.

Abstract: Apparatus and methods for collecting information may include receiving one or more inputs of information related to a business experience. In addition, the apparatus and methods may include storing the received business information. The methods may also include analyzing the received information to generate one or more targeted recommendations; and forwarding the one or more targeted recommendations to management of the business.

Abstract: Technologies are described herein for detecting and recovering from a fire event within an aircraft. The technologies receive sensor data from a number of sensors associated with an aircraft. A determination is made as to whether the sensor data exceeds predefined thresholds indicating the fire event within the aircraft. In response to determining that the sensor data exceeds the predefined thresholds indicating the fire event, the technologies determine a location of the fire event within the aircraft based on the sensor data and depower components of the aircraft associated with the fire event. The technologies then initiate a fire suppressant mechanism within the aircraft directed to the location of the fire event.

Abstract: A method for finding similar search terms (word matching) is provided. The method receives a query of at least a first word and automatically applies the first word to a vocabulary amplifier. The vocabulary amplifier retrieves an associated word for the first word and accesses one or more database sources to retrieve an associated word. Each associated word is presented to an output interface. The amplifier then receives information from an input interface for the associated word and classifies the associated word based upon the received characterizing information.

Abstract: A system, method, and computer program product for combining causal domain models with reasoning and text processing for knowledge driven decision support are provided. A knowledge driven decision support system is capable of creating a domain model, extracting and processing quantities of text according to the domain model, and generating understanding of the content and implications of information sensitive to analysts. An interface may be used to receive input to model complex relationships of a domain, establish implications of interest or request a query, and update the causal model. A processing element can capture and process text into text profiles by incorporating the domain model and process the text profiles in accordance with the domain model by applying formal reasoning to the information to derive trends, predict events, or arrive at other query results. An output element can provide a user the resulting information related to the domain model.

Abstract: A computer-based searching method is described that includes receiving, at a computer, a search concept that includes a plurality of principal words, determining a set of semantically similar words for at least one of the principal words, calculating a degree of membership for each word in each set that reflects a semantic similarity in meaning to the principal word of the set, performing the search, computing a score based at least on the degrees of membership for the words in the word set, and sorting the results using the computed scores.

Abstract: Provided are systems, methods, and computer programs for predicting the likelihood, the extent, and/or the time of an event or change of occurrence using a combination of cognitive causal models with reasoning and text processing for knowledge driven decision support. Additional information may be required for particular queries, such as to predict the extent or time of events and change occurrences. An example knowledge driven decision support system for the prediction of information may include a domain model defining at least two domain concepts and at least one causal relationship between the domain concepts and a reasoning tool for employing the domain model by using at least two of the domain concepts and at least one of the causal relationships of the domain concepts to analyze at least one document for determining a result representing the prediction of an event occurrence, wherein at least one of the causal relationships being used is between two of the domain concepts being used.

Abstract: A diagnostic system and method for enabling multistage decision optimization in aircraft preflight dispatch. The diagnostic system includes an interface for receiving one or more inputs relating to one or more observed symptoms indicative of a failed component in an aircraft. The diagnostic system extends an entropy-based value of information (VOI) diagnostic model by adding an explicit value function into the VOI diagnostic model to accommodate various variables associated with the aircraft preflight dispatch problem. The construction of the entropy-based VOI diagnostic model and thus the extended VOI diagnostic model are both based upon at least one of systemic information relating to aircraft components and input-output relationships of the aircraft components, experience-based information relating to direct relationships between aircraft component failures and observed symptoms, and factual information relating to aircraft component reliability.