Abstract: Systems and methods for automated historical risk assessment for risk mitigation in online access control are provided. An entity assessment server can receive a request to assess a risk indicator change from a first risk indicator to a second risk indicator. For each attribute used to generate the first risk indicator and second risk indicator, a first impact can be determined for changing from the first risk indicator to a third risk indicator between the first risk indicator and the second risk indicator. A second impact similarly can be determined for changing from the third risk indicator to the second risk indicator. Aggregating the first impact and the second impact can determine a total impact of each attribute. Assessment results can be generated to include a list of attributes ordered according to the respective total impact and transmitted to a remote computing device for use in improving the risk indicator.

Abstract: A well tracking device includes a rectangular frame including four sidewalls. The sidewalls define sets of opposing grooves, and the well tracking device is configured to receive or fit on top of a multi-well plate. The well tracking device also includes a well coordinate indicator positioned on an upper portion of the rectangular frame, that includes labels associated with columns and/or rows of the multi-well plate. The well tracking device also includes at least one slider that is configured to interface with a set of opposing grooves and slide along a width or length of the rectangular frame. The slider includes a plurality of openings disposed along the elongated shape of the slider.

Abstract: Various aspects involve a monotonic recurrent neural network (MRNN) trained for risk assessment or other purposes. For instance, the MRNN is trained to compute a risk indicator from a predictor variable. Training the MRNN includes adjusting weights of nodes of the MRNN subject to a set of monotonicity constraints, wherein the set of monotonicity constraints causes output risk indicators computed by the RNN to be a monotonic function of input predictor variables. The trained monotonic RNN can be used to generate an output risk indicator for a target entity.

Abstract: Various aspects involve a monotonic recurrent neural network (MRNN) trained for risk assessment or other purposes. For instance, the MRNN is trained to compute a risk indicator from a predictor variable. Training the MRNN includes adjusting weights of nodes of the MRNN subject to a set of monotonicity constraints, wherein the set of monotonicity constraints causes output risk indicators computed by the RNN to be a monotonic function of input predictor variables. The trained monotonic RNN can be used to generate an output risk indicator for a target entity.

Abstract: There may be situations in which a ship at sea is lost and GPS is not available due to jamming, and neither a position fix nor GPS is available. A system and method allow estimation of ship position (SPOS) using only single radar range measurements and satellite ephemeris data. The same radar can determine ship velocity using radar range rate information.

Abstract: A system and method for performing correlation processing for identifying an object of interest in a cloud of remote objects of different types comprises receiving RF and IR measurement data including rotational, translational bias and noise errors and determining and removing biases by minimizing a weighted distance metric. Correlation pairing metrics are then determined according to a maximum likelihood criteria. This method produces a correlation solution that minimizes the effects of biases and random noise while accounting for the statistical properties of the parameters being estimated.

Abstract: A system and method for determining a 3-dimensional target position and velocity using 2-dimensional IR sensor angular measurements for objects travelling in a ballistic manner within an IR sensor's field of view (FOV). Resulting 3-dimensional states may be used to generate updated inputs for correlation and object selection to drive missile guidance and intercept operations.

Abstract: There may be situations in which a ship at sea is lost and GPS is not available due to jamming, and neither a position fix nor GPS is available, or the heading and attitude sensors are degraded. A system and method allow estimating a ship's heading and pitch using radar range measurements, multiple antennas and satellite ephemeris data.

Abstract: A system for engaging hostile air or space threats with a defensive missile, where the defensive missile comprises an antenna for receiving global positioning system (GPS) signals. A global positioning system receiver is coupled to said antenna, for receiving global positioning system signals directly from global positioning system satellites and global positioning system signals reflected from the threat. A processing arrangement processes the direct and reflected global positioning system signals for determining the position and velocity of the threat. Vectoring controls are coupled to the processing arrangement, and are responsive to the location of the threat for directing the defensive missile toward the threat. In a particular embodiment, the antenna of the defensive missile is directionally controllable, and the defensive missile includes an antenna direction controller responsive to the processor for directing at least a beam of the antenna toward the threat.

Abstract: A method determines the atmospheric refraction of a radar beam by utilizing a stabilized optical telescope directed toward a star near the radar target location. This allows measuring the target refraction as observed from ships at sea without a-priori knowledge of the local refraction index or weather conditions in the target area. The telescope may employ an infra-red (IR) sensor and is capable of imaging stars. The atmospheric refraction of the star light is determined by pointing the telescope based on star ephemeris data, and measuring the star image deviation from the center of the telescope's field-of-view (FOV). The corresponding refraction of the radar beam can be determined by employing a conversion factor relating the IR-to-RF atmospheric propagation characteristics. This conversion factor can be obtained by dedicated tracking measurements.