Abstract: A maritime vehicle includes a surface for contacting a fluid medium through which the maritime vehicle is propelled. The maritime vehicle also includes an array of transducers and a controller. The transducers in the array are arranged across the maritime vehicle's surface for generating pressure waves in the fluid medium. Each transducer in the array is arranged to vibrate for generating a respective pressure wave, which propagates away from the surface in the fluid medium. The controller vibrates the transducers in the array so that the pressure waves control the drag of the maritime vehicle from the fluid medium.

Abstract: A vehicle includes a surface for contacting a fluid medium through which the vehicle is propelled. The vehicle also includes an array of transducers and a controller. The transducers in the array are arranged across the vehicle's surface for generating pressure waves in the fluid medium. Each transducer in the array is arranged to vibrate for generating a respective pressure wave, which propagates away from the surface in the fluid medium. The controller vibrates the transducers in the array so that the pressure waves control the drag of the vehicle from the fluid medium.

Abstract: A neural network system, involving a neural network, the neural network configured to: map sensor output to a Level 1 input; learn to fuse the time slices for one class, learning comprising taking and feeding a random assignment of inputs from each time slice into a threshold function for another two-dimensional array; learn to reject class bias for completing network training; use cycles for class recognition, and fuse segments for intelligent information dominance and a magnetic headwear apparatus operably coupled with the neural network.

Abstract: A vehicle includes a surface for contacting a fluid medium through which the vehicle is propelled. The vehicle also includes an array of transducers and a controller. The transducers in the array are arranged across the vehicle's surface for generating pressure waves in the fluid medium. Each transducer in the array is arranged to vibrate for generating a respective pressure wave, which propagates away from the surface in the fluid medium. The controller vibrates the transducers in the array so that the pressure waves control the drag of the vehicle from the fluid medium.

Abstract: Actions may be automatically determined by a machine learning system using transformational randomization. A situation set and an action sequence associated with contexts of a computer-implemented application may be obtained. Left-hand side (LHS) equivalence transformations and right-hand side (RHS) equivalence transformations are obtained based on a set of a plurality of rules for the application. LHS randomizations are obtained based on combining the plurality of LHS equivalence transformations. RHS randomizations are obtained based on combining the plurality of RHS equivalence transformations. A randomized context is obtained based on the LHS randomizations, and an action sequence is determined based on the context randomization. A randomized action sequence is obtained based on the RHS randomizations. A valid action is determined based on a probability value of a randomized rule associated with the randomized action sequence.

Abstract: A device, method, and system for synthesizing variants of semantically equivalent computer source code using computer source code components to protect against cyberattacks. An input constraint, an output constraint, and a schema are received from a user. A component-based synthesizer generates first computer source code including a first computer source code component based on the input constraint, the output constraint, and the schema. The component-based synthesizer generates second computer source code including a second computer source code component based on the input constraint, the output constraint, and the schema. The second computer source code is generated as a semantically equivalent variant of the first computer source code to provide for protection against a cyberattack. The invention may also include a dynamic component library.

Abstract: A method includes providing a set of deep learning neural networks where no pair of deep learning neural networks within the set of deep learning neural networks produces a semantically equivalent output by design. An input to the set of deep learning neural networks is provided, where responsive to the input, one or more of the deep learning neural networks produces an output. The output of the deep learning neural networks is input into a case-based reasoning (CBR) system. The CBR system generates an output responsive to the input received by the CBR system if the input received by the CBR system is known by the CBR system. The output of the CBR system is then determined to be a correct/incorrect output. One of the deep learning neural networks is trained on the correct output if the correct output is specific to the particular deep learning neural network.

Abstract: An artificial intelligence system and a method for its operation include rule bases established to maintain rules for respective knowledge domains. A network links the rule bases together. A first rule in every rule base references a second rule in another rule base via the network, and the network at least interconnects every first and second rule bases for which the first rule in the first rule base references the second rule in the second rule base. The artificial intelligence system is adapted to invoke a third one of the rules of a particular one of the rule bases in response to an input from a user of the artificial intelligence system, and this begins a chain invoking the rules of the rule bases via the network. The chain includes the first rule in one of the rule bases invoking the second rule in another one of the rule bases.

Abstract: A vehicle includes a surface for contacting a fluid medium through which the vehicle is propelled. The vehicle also includes an array of transducers and a controller. The transducers in the array are arranged across the vehicle's surface for generating pressure waves in the fluid medium. Each transducer in the array is arranged to vibrate for generating a respective pressure wave, which propagates away from the surface in the fluid medium. The controller vibrates the transducers in the array so that the pressure waves control the drag of the vehicle from the fluid medium.

Abstract: Actions may be automatically determined by a machine learning system using transformational randomization. A situation set and an action sequence associated with contexts of a computer-implemented application may be obtained. Left-hand side (LHS) equivalence transformations and right-hand side (RHS) equivalence transformations are obtained based on a set of a plurality of rules for the application. LHS randomizations are obtained based on combining the plurality of LHS equivalence transformations. RHS randomizations are obtained based on combining the plurality of RHS equivalence transformations. A randomized context is obtained based on the LHS randomizations, and an action sequence is determined based on the context randomization. A randomized action sequence is obtained based on the RHS randomizations. A valid action is determined based on a probability value of a randomized rule associated with the randomized action sequence.

Abstract: A computational system for solving a non-deterministic polynomial problem, involving a parellel processor operable by a set of self-updatable executable instructions storable on a non-transient memory device and configuring the parallel processor to interface with an information acquisition program, heuristically acquire information, through the information acquisition program, via a first transference and a second transference, whereby heuristic information is acquired, parametrically evolve the heuristic information, whereby parametrically evolved heuristic information is provided, reuse the parametrically evolved heuristic information to further heuristically acquire information, whereby iterative parametrically evolved heuristic information is provided, and self-update the set of executable instructions based on the iterative parametrically evolved heuristic information, whereby a self-updated set of executable instructions is provided, whereby the self-updated set of executable instructions facilitates i

Abstract: Case-based information is randomized to rule-based information by accessing a case base to obtain a plurality of sets of variables representing case-based input/output constraints associated with corresponding cases. A matching is initiated, of a candidate case with one or more contexts of items included in a knowledge repository storing a plurality of cases and a plurality of rules that are organized in segments according to a plurality of domains and are comingled. At least one of the cases of the plurality of cases is generalized.

Abstract: An input constraint, an output constraint, and a schema are received from a user. A component-based synthesizer generates first computer source code including a first computer source code component based on the input constraint, the output constraint, and the schema. The component-based synthesizer generates second computer source code including a second computer source code component based on the input constraint, the output constraint, and the schema. The second computer source code is generated as a semantically equivalent variant of the first computer source code to provide for protection against a cyberattack.

Abstract: A neural network system, involving a neural network, the neural network configured to: map sensor output to a Level 1 input; learn to fuse the time slices for one class, learning comprising taking and feeding a random assignment of inputs from each time slice into a threshold function for another two-dimensional array; learn to reject class bias for completing network training; use cycles for class recognition, and fuse segments for intelligent information dominance and a magnetic headwear apparatus operably coupled with the neural network.

Abstract: A computing device learns a natural language. A mapper included in the computing device non-deterministically maps an input natural language sentential form to a matching semantic that is associated with a computer language function component. A translator included in the computing device translates the matching semantic into a translated natural language sentential form.

Abstract: A cyber-security validator stores first computer source code and second computer source code received via an interface in a memory. The cyber-security validator compares the first computer source code and the second computer source code during at least one stage from storage through compilation and execution. The cyber-security validator determines whether a cyberattack has occurred or is in progress based on results of the comparison.

Abstract: A method involves providing an information base comprising a plurality of domain-specific segments, each segment comprising a case base having cases therein and a transform base having transforms therein. Each case comprises a case antecedent and a case consequent. One or more cases are associated with one or more of transforms within the respective segment. A contextual situation falling within one of the domain-specific segments is then received and it is determined that the received contextual situation does not match the case antecedent of any of the cases within the particular domain-specific segment. One or more transforms are applied to one or more cases within the segment to create a transformed case. The transformed case has a case antecedent that matches the contextual situation and a case consequent. The case consequent of the transformed case is displayed to a user and the transformed case is stored in the case base.

Abstract: First and second computer source codes are generated by a case-based inference engine based on first and second parameters received via a user interface. The first and second parameters are different but are both associated with a desired result. The second computer source code is generated as a semantically equivalent variant of the first computer source code to provide for protection against a cyber-attack.

Abstract: A computing device learns a natural language. A mapper included in the computing device non-deterministically maps an input natural language sentential form to a matching semantic that is associated with a computer language function component. A translator included in the computing device translates the matching semantic into a translated natural language sentential form.

Abstract: A system uses arrays of spatial light modulators (SLMs) connected to a processor and an image capture device. An image is input into a first array of SLMs. The processor determines if the output of the first array matches an image stored within a database. If a match is found, the processor outputs a stored image to an image processing system. If a match is not found the processor directs the output from the first array into an input of an array of SLMs adjacent to the first array. The determination step is iteratively performed for the remaining arrays of SLMs until a match is found or no arrays remain. If no arrays remain, the processor selects a stored image from the database and obtains user feedback from a user input system. The feedback is then stored in the database and associated with the n?1 array of SLMs.