Abstract: A system includes a computer to implement a front-end input condensation program and a back-end machine learning program. Steps of the front-end program include receive input data and time data indicative of previous events associated with users; determine interface channels associated with modes of interface with the users and/or previous event characteristics; associate previous event data with time windows; generate user window values for the combinations of users and time windows indicating the interface channels and previous event characteristics of data within the respective time windows; and form condensed input data without raw input data having a low association with respect to preceding the subsequent event. Steps of the back-end program include receive the condensed input data and use the condensed data to generate an inference related to the subsequent event such that a time required by the machine learning algorithm to generate the inference is reduced.

Abstract: A system for reducing the time to train a machine learning program for predicting a subsequent event. The system includes a computer configured to implement instructions to receive training data and time data indicative of training events associated with users. The instructions configure the system to determine interface channels associated with modes of interface with the users, training event characteristics, or both. The system implements instructions associating training event data with time windows. The instructions configure the system to generate user window values for the combinations of users and time windows. The user window values indicate the interface channels and training event characteristics of data within the respective time windows. Implementing the instructions configures the system to form a first portion of the raw input data having an association value below a threshold with respect to preceding the subsequent event and generate condensed training data.

Abstract: A message generating system disseminates to each of multiple user devices first information items each associated with at least a respective one of multiple services made available by a first entity. When access indicative signals are received via a network connection, each prompted by a respective one of the user devices accessing at least one of the first information items, the system stores a respective awareness-stage record for each received access indicative signal, thereby recording that the respective user entity accessed at least one of the first information items. For each user entity for which a respective awareness-stage record is stored, a second item is generated and sent including information of a particular service associated with at least one first information item. User entities for which a second item was not generated are excluded as having not accessed a first item. The exclusion reduces data traffic on the network connection.

Abstract: A system for guiding interactions with a user device requests a response from a plurality of users, stores the response as response data forming a subset of a personal data set of each of the responding users, and generates a predictive model during training of a machine learning program utilizing at least one neural network with a training data set including the personal data set of each of the plurality of users. The predictive model predicts a probability of a first one of the users associated with the user device interacting with a first product and/or service by correlating a personal data set of the first one of the users to the personal data set of at least a second one of the users and sends a communication relating to the first product and/or service to the user device when the predicted probability meets or exceeds a threshold value.

Abstract: A system and method for training an artificial intelligence engine for real-time monitoring to eliminate false positives is disclosed. The system includes at least one processor, a communication interface coupled to the processor, and a memory device storing executable code. Executing the executable code causes the processor to receive data from an AI security model, receive data from a false positive database, and correlate both sets of data. The correlated data is used to generate a training dataset and a test dataset used to train a false positive identification model. After evaluating the false positive identification model, an AI engine is applied to user registration. The AI engine includes an AI security model and the false positive identification model. Additionally, a system for evaluating the security of user registration utilizing the false positive identification model is disclosed.

Abstract: A system for guiding interactions with a user device requests a response from first users, stores the response as response data forming a subset of a personal data set of each of the responding first users, and generates a predictive model during training of a machine learning program with a training data set including the personal data set of each of the first users. The predictive model predicts a predicted response of a second user associated with the user device by correlating a personal data set of the second user to the personal data set of at least one of the first users. The computer sends a communication to the user device of the second user having content relating to the first product and/or service when it is determined that the predicted response indicates an interest in or preference of the second user for the first product and/or service.

Abstract: A system for reducing input data size for use in an artificial intelligence (AI) engine for predicting a subsequent event. The system includes a computer configured to implement instructions to receive input data and time data indicative of previous events associated with users. The instructions configure the system to determine interface channels associated with modes of interface with the users, previous event characteristics, or both. The system implements instructions associating previous event data with time windows. The instructions configure the system to generate user window values for the combinations of users and time windows. The user window values indicate the interface channels and previous event characteristics of data within the respective time windows. Implementing the instructions configures the system to form a first portion of the raw input data having an association value below a threshold with respect to preceding the subsequent event and generate condensed input data.

Abstract: A system for guiding interactions with a user device requests a response from a plurality of users, stores the response as response data forming a subset of a personal data set of each of the responding users, and generates a predictive model during training of a machine learning program utilizing at least one neural network with a training data set including the personal data set of each of the plurality of users. The predictive model predicts a probability of a first one of the users associated with the user device interacting with a first product and/or service by correlating a personal data set of the first one of the users to the personal data set of at least a second one of the users and sends a communication relating to the first product and/or service to the user device when the predicted probability meets or exceeds a threshold value.

Abstract: A message generating system disseminates to each of multiple user devices first information items each associated with at least a respective one of multiple services made available by a first entity. When access indicative signals are received via a network connection, each prompted by a respective one of the user devices accessing at least one of the first information items, the system stores a respective awareness-stage record for each received access indicative signal, thereby recording that the respective user entity accessed at least one of the first information items. For each user entity for which a respective awareness-stage record is stored, a second item is generated and sent including information of a particular service associated with at least one first information item. User entities for which a second item was not generated are excluded as having not accessed a first item. The exclusion reduces data traffic on the network connection.

Abstract: Aerial vehicles are assigned to routes within a transportation network based on a state of charge, state of power, and/or state of health for the aerial vehicle. Such aspects can be modeled based on one or more statistical models and/or machine-learned models, among other examples. As another example, an energy budget is used to ensure that the state of charge, state of power, and/or state of health of the aerial vehicle during and/or after traveling the route remains within the energy budget. A payload is assigned to a route and an associated aerial vehicle, thereby generating an itinerary. In examples, the itinerary is validated by the aerial vehicle to ensure that the aerial vehicle is capable of traveling the route with the payload. In examples where the aerial vehicle rejects the itinerary, the itinerary is assigned to another aerial vehicle and a new itinerary is identified for the aerial vehicle.

Abstract: Methods of producing a plurality of distinguishably fluorescently barcoded particle, e.g., cellular, bead, etc., samples, e.g., for use in the multiplex flow cytometric workflows, are provided. Aspects of the methods include: providing a plurality of particle, e.g., cellular, bead, etc., samples; and labeling different particle, e.g., cellular, bead, etc., samples of the plurality with unique fluorescent barcodes, wherein a given fluorescent barcode comprises one or more fluorescently labeled specific binding members that specifically bind to a particle marker. Also provided are compositions for practicing methods of the invention.

Abstract: Methods, systems, and apparatus, including medium-encoded computer program products, for computer aided design of physical structures using generative design processes. A method includes obtaining one or more load cases and one or more design criteria for a modeled object, the one or more design criteria comprising a build material strength model indicating strength relationships between thickness of an object feature and build angle for that object feature resulting from additive manufacturing; iteratively modifying a three dimensional shape of the modeled object in accordance with the one or more design criteria and the one or more load cases, including applying the strength relationships between the thickness of the object feature and the build angle for that object feature on a per-element basis during numerical simulation of the modeled object; and providing the three dimensional shape of the modeled object for use in manufacturing a physical structure.

Abstract: A memory system may include separate amounts or types of resistive material that may be deposited over memory cells and conductive vias using separate resistive layers in the access lines. A first resistive material layer may be deposited over the memory cells prior to performing an array termination etch used to deposit the conductive via. The array termination etch may remove the first resistive material over the portion of the array used to deposit the conductive via. A second resistive material layer may be deposited after the etch has occurred and the conductive via has been formed. The second resistive material layer may be deposited over the conductive via.

Abstract: An optical stimulation system includes a light source configured to produce light for optical stimulation; a light monitor; an optical lead coupled, or coupleable, to the light source and the light monitor; and a control module coupled, or coupleable, to the light source and the light monitor. The control module includes a memory, and a processor coupled to the memory and configured for receiving a request for verification or measurement of a light output value; in response to the request, receiving, from the light monitor, a measurement of light generated by the light source; and, based on the measurement, reporting a response to the request.

Abstract: A server operates between a patron (user), a subscriber (e.g., owner of a venue of exhibits and its website; museum, stadium, zoo, theme park, etc.), and possibly third parties such as a content distribution network (CDN). Access and content delivery are based on 1) control information provided to a patron device by physical objects at the venue and sent by the patron device to the server as part of a mutual authentication to one another, 2) user-specific information corresponding to the patron device, and 3) a pre-authorization exchange granting user-device access to physical objects and the server with the server receiving access to the user-specific information in order to locate requested information and select a subset thereof adapted in accordance with the user information. Moving physically between exhibits, a patron device rapidly disengages and re-engages the server, based thereon, without repeated logins.

Abstract: A silicate-based composition includes, in mol.%: 35-65% SiO2, 20-40% CaO, 10-30% Na2O, 0-15% TiO2, >0-15% Al2O3, 0-10% P2O5, 0-15% ZrO2, and 0-3% SnO2. A method of forming a silicate-based composition includes ceramming a silicate-based composition such that the ceramming is a cycle has a first portion and a second portion, with the first portion conducted at a first temperature for a first time and the second portion conducted at a second temperature for a second time.

Abstract: A support assembly includes a support surface configured to selectively transition between a stowed position, a deployed position, and an intermediate position defined between the stowed position and the deployed position. A retention feature is operably coupled to the support surface and is configured to transition the support surface between the stowed position and the deployed position. The retention feature includes a projection about which the support surface pivots to define a pivot axis. A bracket is coupled to the support surface and is configured to distribute a load along the support assembly in the intermediate position and the deployed position.

Abstract: An embodiment includes analyzing data associated with an original flow graph comprising a plurality of operators of a stream computing application, including identifying a secure network connection between a first operator and a second operator that uses encryption. The embodiment fuses the first operator with the second operator such that a first logical function of the first operator is combined with a second logical function of the second operator. The embodiment then generates a modified flow graph as a modification of the original flow graph that combines the first operator and the second operator and lacks encryption between the first operator and the second operator.

Abstract: Methods, systems, and apparatus, including medium-encoded computer program products, for computer aided design with feature thickness control, include: a three-dimensional modeling program configured to provide voxelized thinning based distance to medial surface processing that measures thicknesses in a three-dimensional model, and/or ramped scaling based thickness constraint application during shape and/or topology generation. The three-dimensional modeling program can be an architecture, engineering and/or construction program (e.g., building information management program), a product design and/or manufacturing program (e.g., a CAM program), and/or a media and/or entertainment production program (e.g., an animation production program).

Abstract: Methods, systems, and apparatus, including medium-encoded computer program products, for computer aided design of physical structures using generative design processes. A method includes performing numerical simulation of a modeled object in accordance with a current version of the three dimensional shape and the one or more in-use load cases; finding a maximized stress or strain element, for each in-use load cases; determining an expected number of loading cycles for each of the one or more in-use load cases for the physical structure using the maximized stress or strain element and data relating fatigue strength to loading cycles; redefining a fatigue safety factor inequality constraint for the modeled object; computing shape change velocities for an implicit surface in a level-set representation of the three dimensional shape in accordance with at least the fatigue safety factor inequality constraint; and updating the level-set representation using the shape change velocities.