Abstract: Real-time condition-based analysis is performed on a machine for providing diagnostic and prognostic outputs indicative of machine status includes a signal processor for receiving signals from sensors adapted for measuring machine performance parameters. The signal processor conditions and shapes at least some of the received signals into an input form for a neural network. A fuzzy adaptive resonance theory neural network receives at least some of the conditioned and shaped signals, and detects and classifies a state of the machine based upon the received conditioned and shaped signals, and upon a predetermined ontology of machine states, diagnostics, and prognostics. The neural network can also determine from the machine state a health status thereof, which can comprise an anomaly, and output a signal representative of the determined health status. A Bayesian intelligence network receives the machine state from the neural network and determines a fault probability at a future time.

Abstract: A display assembly (515) includes: (a) an image display system (10) which includes an array of pixels (120) and (b) an array of pixel lenses (115). The array of pixel lenses has each lens positioned to collimate or substantially collimate light from a corresponding single pixel of the array of pixels. The display assembly (515) is used in a head-mounted display apparatus (500) which includes a frame (510) to support the display assembly (515) a desired distance from a user's eyes. The head-mounted display apparatus may also include a beam splitter (520) to reflect images from the display assembly (515) to the user's eyes. The head-mounted display apparatus may provide a wide field of view to the user and may be of the augmented-reality or immersive type.

Abstract: Computer-based methods and associated computer systems are disclosed for designing free space reflective optical surfaces (13) for use in head-mounted displays (HMDs). The reflective optical surface (13) produces a virtual image of a display surface (11) for viewing by a user's eye (15). The method includes using one or more computers to: (i) represent the display surface (11) by display objects (25); (ii) represent the free space reflective optical surface (13) by surface elements (23); and (iii) iteratively calculate spatial locations, normals, and radii of curvature for the surface elements (23) which will cause a virtual image of each display object (25) to be displayed to a nominal user's eye (15) in a desired direction of gaze of the eye (15).

Abstract: Head-mounted displays (100) are disclosed which include a frame (107), an image display system (110) supported by the frame (107), and a Fresnel lens system (115) supported by the frame (107). The HMD (100) can employ a reflective optical surface, e.g., a free-space, ultra-wide angle, reflective optical surface (a FS/UWA/RO surface) (120), supported by the frame (107), with the Fresnel lens system (115) being located between the image display system (110) and the reflective optical surface (120). The Fresnel lens system (115) can include at least one curved Fresnel lens element (820). Fresnel lens elements (30) for use in HMDs are also disclosed which have facets (31) separated by edges (32) which lie along radial lines (33) which during use of the HMD pass through a center of rotation (34) of a nominal user's eye (35) or through the center of the eye's lens (36) or are normal to the surface of the eye's cornea.

Abstract: Head-mounted displays (100) are disclosed which include a frame (107), an image display system (110) supported by the frame (107), and a reflective surface, e.g., a free-space, ultra-wide angle, reflective optical surface (a FS/UWA/RO surface) (120), supported by the frame (107). In certain embodiments, the reflective surface (120) produces spatially-separated virtual images that are angularly separated by at least 100, 150, or 200 degrees. Methods and apparatus for designing reflective optical surfaces, including FS/UWA/RO surfaces, for use in head-mounted displays (100) are also disclosed.

Abstract: A system, method, and computer-readable instructions for real-time characters with learning capabilities. A plurality of rules are defined in a rules-based system, each of the rules defining a condition that determines a behavior of a virtual agent when the rule is triggered by the condition being satisfied so that upon triggering of multiple rules at the same time, each of the behaviors of the multiple rules whose conditions were satisfied are combined into a resultant behavior for the virtual agent. This resultant behavior is compared with a desired behavior to providing feedback in the form of rewards or punishments to each of the multiple rules based on their corresponding contribution to the resultant behavior as compared to the desired behavior.

Abstract: Systems and methods for recording impression events of Ad content on a webpage. An example method renders on a display of a computer device a webpage accessible over a network. The webpage includes at least one Ad unit. Then Ad tag information associated with the at least one Ad unit and browser viewport information (display location and size information) is retrieved. The occurrence of an Ad Placement event is determined if based on the comparison a predefined percentage of the Ad unit is within the browser viewport. An Ad Placement event timer is begun upon the determination of occurrence of the Ad Placement event. The Ad Placement event timer is stopped if an out-of-view event has occurred based on the Ad tag information and the browser viewport information. An Ad Placement event is then recorded. The recorded Ad Placement event is transmitted to a previously designated server over the network.

Abstract: Systems and methods for determining delivery hierarchical information for an Ad unit. In an example method performed at a server, location information is received from a user computer system via a network. The location information is associated with an Ad unit presented on a webpage accessed by the user computer system. The server determines if any previously stored signature information matches with at least a portion of the received location information, then extracts domain information for any portions of the received location information that matches with any previously stored signature information. Then, at least partial delivery hierarchical information is generated based on the extracted domain information. The process repeats for other location information associated with the Ad unit that is received at the server. The generated delivery hierarchical information is aggregated. Then a report is generated based on the aggregated delivery hierarchical information.

Abstract: Systems and methods for capturing user engagements with Ad content included in a webpage. An example method renders a webpage having an Ad unit within a browser on a display of a user's computer. Then, a cursor event for an Ad unit included in the rendered webpage is recorded based on cursor position relative to an area on the webpage associated with the Ad unit and the recorded cursor event is transmitted to a server via a network for reporting to interested parties. The cursor event includes an initial cursor entry event, any click actions or any hover actions, and all related timings of such events. The recordation of a cursor event is further based on location information associated with the browser within the display, the webpage within the browser and the ad area within the webpage.

Abstract: A neural network learns the operating modes of a system being monitored under normal operating conditions. Anomalies can be automatically detected and learned. A control command can be issued or an alert can be issued in response thereto.

Abstract: A method for determining a root cause of a problem in a multiple-element system includes correlating an incoming alarm signal with an element x in a multiple-element system and accessing an implication list comprising a list of all elements upstream of element x. At least one element on the implication list is weighted with data relating to the at least one element. Taking into account the weighting step, a probability is calculated that an element on the implication list comprises a most-probable root cause of the subsequent alarm signal. The identified most-probable root cause of the incoming alarm signal is output.

Abstract: Real-time condition-based analysis is performed on a machine for providing diagnostic and prognostic outputs indicative of machine status includes a signal processor for receiving signals from sensors adapted for measuring machine performance parameters. The signal processor conditions and shapes at least some of the received signals into an input form for a neural network. A fuzzy adaptive resonance theory neural network receives at least some of the conditioned and shaped signals, and detects and classifies a state of the machine based upon the received conditioned and shaped signals, and upon a predetermined ontology of machine states, diagnostics, and prognostics. The neural network can also determine from the machine state a health status thereof, which can comprise an anomaly, and output a signal representative of the determined health status. A Bayesian intelligence network receives the machine state from the neural network and determines a fault probability at a future time.

Abstract: Methods and systems of achieving contextual ad serving, without the need for this expansive infrastructure of storing every possible hosting URL, and ensuring always-current page context by evaluating the context of the hosting page/URL in real-time, for every ad impression. This is achievable by reversing the model by identifying the corpus of all terms relevant to the available ad inventory (i.e. a selective set of terms) rather than attempting to evaluate the corpus of all terms residing in the hosting page/URL.

Abstract: A neural network learns the operating modes of a system being monitored under normal operating conditions. Anomalies can be automatically detected and learned. A control command can be issued or an alert can be issued in response thereto.

Abstract: A neural network learns the operating modes of a system being monitored under normal operating conditions. Anomalies can be automatically detected and learned. A control command can be issued or an alert can be issued in response thereto.

Abstract: A multi-processor synchronized simulation system that incorporates a common control element which generates common start frame messages for the various simulating systems. A start frame message will not be transmitted by the control element until all entity data from a prior frame has been sent to the appropriate simulation system. Each respective system, in response to the start frame message, then executes its next interval of frame processing and issues a frame complete message to the control element. The element in turn issues a subsequent start frame message only when all of the simulation systems have provided a respective frame complete message.

Abstract: A neural network learns the operating modes of a system being monitored under normal operating conditions. Anomalies can be automatically detected and learned. A control command can be issued or an alert can be issued in response thereto.

Abstract: Systems and methods for parallel, discrete, simulations include functional capabilities to incorporate one or more human operators or actors into the simulation process. Such individuals can be presented situations where one or more decisions are necessary with respect to ongoing events. Entered decisions are incorporated into simulated events and activities being simulated. These in turn influence the behavior of those entities and also initiate the occurrence of other time-based processes. An architecture artifact or product can be automatically created or updated by recording how a sequence of events took place. The creation of sections of the DoDAF OV-6C Operational Event Trace architectural diagram, for the executable architecture model, can be automatically performed to dynamically provide event traces in response to a live exercise.

Abstract: A neural network learns the operating modes of a system being monitored under normal operating conditions. Anomalies can be automatically detected and learned. A control command can be issued or an alert can be issued in response thereto.

Abstract: A neural network learns the operating modes of a system being monitored under normal operating conditions. Anomalies can be automatically detected and learned. A control command can be issued or an alert can be issued in response thereto.