Abstract: Foot support systems include a fluid flow control system that facilitates movement of fluid into, out of, and/or within a sole structure and/or article of footwear, e.g., to change and/or control pressure in fluid filled bladder(s). Aspects of this technology may relate to one or more of: (a) footwear structures in which such systems are incorporated; (b) valve stem based fluid flow transfer systems; (c) solenoid based fluid flow transfer systems; (d) user input button features; (e) air filter features; (f) fluid tube to fluid distributor connection features; (g) fluid distributor to footwear connection features; (h) valve position sensor features; (i) valve transmission features; (j) pressure control algorithm features; (k) electronic communication features; (l) system sealing features; and/or (m) pressure sensor mounting features.

Abstract: Foot support systems include a fluid flow control system that facilitates movement of fluid into, out of, and/or within a sole structure and/or article of footwear, e.g., to change and/or control pressure in fluid filled bladder(s). Aspects of this technology may relate to one or more of: (a) footwear structures in which such systems are incorporated; (b) valve stem based fluid flow transfer systems; (c) solenoid based fluid flow transfer systems; (d) user input button features; (e) air filter features; (f) fluid tube to fluid distributor connection features; (g) fluid distributor to footwear connection features; (h) valve position sensor features; (i) valve transmission features; (j) pressure control algorithm features; (k) electronic communication features; (l) system sealing features; and/or (m) pressure sensor mounting features.

Abstract: An authoritative domain name system (DNS) server receives DNS requests for domains. The authoritative DNS server transmits DNS responses to the DNS requests with address records that include IP addresses that are selected from a larger pool of IP addresses, where a first DNS response can include IP addresses different from IP addresses included in a second DNS response for the same domain. Also, the same IP addresses may be returned for a first domain and a different, second domain. The authoritative DNS server may select the IP addresses to include in DNS responses to the DNS requests using a round-robin process.

Abstract: Systems and methods for rendering spatial audio in accordance with embodiments of the invention are illustrated. One embodiment includes a spatial audio system, including a primary network connected speaker, including a plurality of sets of drivers, where each set of drivers is oriented in a different direction, a processor system, memory containing an audio player application, wherein the audio player application configures the processor system to obtain an audio source stream from an audio source via the network interface, spatially encode the audio source, decode the spatially encoded audio source to obtain driver inputs for the individual drivers in the plurality of sets of drivers, where the driver inputs cause the drivers to generate directional audio.

Abstract: Foot support systems include a fluid flow control system that facilitates movement of fluid into, out of, and/or within a sole structure and/or article of footwear, e.g., to change and/or control pressure in fluid filled bladder(s). Aspects of this technology may relate to one or more of: (a) footwear structures in which such systems are incorporated; (b) valve stem based fluid flow transfer systems; (c) solenoid based fluid flow transfer systems; (d) user input button features; (e) air filter features; (f) fluid tube to fluid distributor connection features; (g) fluid distributor to footwear connection features; (h) valve position sensor features; (i) valve transmission features; (j) pressure control algorithm features; (k) electronic communication features; (l) system sealing features; and/or (m) pressure sensor mounting features.

Abstract: Foot support systems include a fluid flow control system that facilitates movement of fluid into, out of, and/or within a sole structure and/or article of footwear, e.g., to change and/or control pressure in fluid filled bladder(s). Aspects of this technology may relate to one or more of: (a) footwear structures in which such systems are incorporated; (b) valve stem based fluid flow transfer systems; (c) solenoid based fluid flow transfer systems; (d) user input button features; (e) air filter features; (f) fluid tube to fluid distributor connection features; (g) fluid distributor to footwear connection features; (h) valve position sensor features; (i) valve transmission features; (j) pressure control algorithm features; (k) electronic communication features; (l) system sealing features; and/or (m) pressure sensor mounting features.

Abstract: A request is received from a client device over a Virtual Private Network (VPN) tunnel. The request is received at a first one of a plurality of edge servers of a distributed cloud computing network. A destination of the request is determined and an optimized route for transmitting the request toward an origin server is determined. The optimized route is based at least in part on probe data between edge servers of the distributed cloud computing network. The request is transmitted to a next hop as defined by the optimized route.

Abstract: The AI engine operates with the common API. The common API supports i) any of multiple different training sources and/or prediction sources installed on ii) potentially different sets of customer computing hardware in a plurality of on-premises' environments, where the training sources, prediction sources as well as the set of customer computing hardware may differ amongst the on-premises' environments. The common API via its cooperation with a library of base classes is configured to allow users and third-party developers to interface with the AI-engine modules of the AI engine in an easy and predictable manner through the three or more base classes available from the library. The common API via its cooperation with the library of base classes is configured to be adaptable to the different kinds of training sources, prediction sources, and the different sets of hardware found a particular on-premises environment.

Abstract: Foot support systems include a fluid flow control system that facilitates movement of fluid into, out of, and/or within a sole structure and/or article of footwear, e.g., to change and/or control pressure in fluid filled bladder(s). Aspects of this technology may relate to one or more of: (a) footwear structures in which such systems are incorporated; (b) valve stem based fluid flow transfer systems; (c) solenoid based fluid flow transfer systems; (d) user input button features; (e) air filter features; (f) fluid tube to fluid distributor connection features; (g) fluid distributor to footwear connection features; (h) valve position sensor features; (i) valve transmission features; (j) pressure control algorithm features; (k) electronic communication features; (l) system sealing features; and/or (m) pressure sensor mounting features.

Abstract: Described are methods, devices, and systems useful for adsorbing organometallic vapor onto solid adsorbent material to remove the organometallic vapor from a gas mixture that contains the organometallic vapor and other vapor, particulate materials, or both.

Abstract: An AI engine having an architect module to create a number of nodes and how the nodes are connected in a graph of concept nodes that make up a resulting AI model. The architect module also creates a first concept node by wrapping an external entity of code into a software container with an interface configured to exchange information in a protocol of a software language used by the external entity of code. The architect module also creates a second concept node derived from its description in a scripted file coded in a pedagogical programming language, and connects the second concept node into the graph of nodes in the resulting AI model.

Abstract: A method for automatically detecting the data type of data in a column includes receiving a request to import data into a base and determining the data type of the column by applying a set of inferrers to the column. In response to an inferrer returning true, the method selects the data type corresponding to the inferrer as the data type of the column and casts the data in the column to the selected type. A method for importing, converting, and presenting data based on data loss metrics includes receiving a request to import data into a database and determining data loss metrics for each of a set of data types. A user interface is configured to display some of the data types in conjunction with data loss metrics. The method further includes receiving a selection of one of the data types and casting the data to the selected type.

Abstract: Foot support systems include a fluid flow control system that facilitates movement of fluid into, out of, and/or within a sole structure and/or article of footwear, e.g., to change and/or control pressure in fluid filled bladder(s). Aspects of this technology may relate to one or more of: (a) footwear structures in which such systems are incorporated; (b) valve stem based fluid flow transfer systems; (c) solenoid based fluid flow transfer systems; (d) user input button features; (e) air filter features; (f) fluid tube to fluid distributor connection features; (g) fluid distributor to footwear connection features; (h) valve position sensor features; (i) valve transmission features; (j) pressure control algorithm features; (k) electronic communication features; (l) system sealing features; and/or (m) pressure sensor mounting features.

Abstract: An authoritative DNS server receives DNS requests for domains. The authoritative DNS server responds to the requests with address records that include IP addresses that are selected from a larger pool of IP addresses, where a first response to a DNS query for a domain can include IP addresses different from IP addresses included in a second response for the same domain. Also, the same IP addresses may be returned for a first domain and a different, second domain. The authoritative DNS server may randomly select the IP addresses to include in responses to the requests regardless of the domain.

Abstract: A method of non-destructive detection of surface and near surface abnormalities in a metallic product. The method comprises positioning a sample having a surface under a source of an incident radiation. The surface of the sample is then irradiated with the incident radiation from the source. A scattered radiation is detected and a radiation pattern from the detected scattered radiation is produced. Said radiation pattern is then analysed and the output indicative of the scattered radiation from the sample is produced. Said produced output is then compared with a threshold value, the threshold value indicative of a maximum acceptable detected surface abnormality. Finally, the presence of a surface abnormality is identified when the output exceeds the threshold value.

Abstract: Systems, methods, and other embodiments described herein relate to determining a type and an issue time of a vehicle control command based on an estimated realization delay. In one embodiment, a method includes identifying a first realization delay associated with a first control command and identifying a second realization delay associated with a second control command. The second control command is issued after the first control command is issued. The method includes issuing the first control command at an issue time that is based on the first realization delay and the second realization delay, and realizing the first control command on a vehicle.

Abstract: A proxy server receives, from multiple visitors of multiple client devices, a plurality of requests for actions to be performed on identified network resources belonging to a plurality of origin servers. At least some of the origin servers belong to different domains and are owned by different entities. The proxy server and the origin servers are also owned by different entities. The proxy server analyzes each request it receives to determine whether that request poses a threat and whether the visitor belonging to the request poses a threat. The proxy server blocks those requests from visitors that pose a threat or in which the request itself poses a threat. The proxy server transmits the requests that are not a threat and is from a visitor that is not a threat to the appropriate origin server.

Abstract: The AI engine has a first module that chooses from a library of algorithms to use when automatically assembling and building different learning topologies to solve different concepts making up a resulting AI model. The AI engine may integrate both i) one or more dynamic programming training algorithms and ii) one or more policy optimization algorithms, to build the different learning topologies to solve the different concepts contained with an AI model in order to solve a wide variety of problem types. Each concept contained in the AI model can use a most appropriate approach for achieving a mission of that concept. A learning topology representing a first concept can be built by the first module with a first dynamic programming training algorithm, while a learning topology representing a second concept in the same AI model can be built by the first module with a first policy optimization algorithm.

Abstract: An artificial intelligence (“AI”) engine is disclosed with AI-engine modules and a plurality of learning agents. The AI-engine modules include instructor, learner, and predictor modules. The learner module is configured to train a plurality of AI models in parallel, and the instructor module is configured to coordinate with a plurality of simulators for respectively training the AI models. The learning agents are configured to process training requests from the instructor on data from the simulators for training the AI models. The learner module is further configured to first train the AI models on a first batch of similar data synchronously pooled in a memory of the learner module with a first processor. The learner module is further configured to subsequently train the AI models on a second, different batch of similar data synchronously pooled in the memory of the learner module with the first processor.