Abstract: There are provided systems and methods for a compute platform for machine leaning model roll-out. A service provider, such as an electronic transaction processor for digital transactions, may provide intelligent decision-making through decision services that execute machine learning models. When deploying or updating machine learning models in these engines and decision services, a model package may include multiple models, each of which may have an execution graph required for model execution. When models are tested from proper execution, the models may have non-performant compute items, such as model variables, that lead to improper execution and/or decision-making. A model deployer may determine and flag these compute items as non-performant and may cause these compute items to be skipped or excluded from execution. Further, the model deployer may utilize a pre-production computing environment to generate the execution graphs for the models prior to deployment or upgrading.

Abstract: A sidestep assembly for helping a user entering a cabin of an industrial vehicle, the sidestep assembly comprising a frame comprising an upper member, a lower member on which the user can step for accessing and exiting the cabin, and an elastic member, in which the upper member is configured to be fixed to the industrial vehicle by the elastic member so that the frame can be elastically displaced relative to the cabin when the frame is impacted by an obstacle.

Abstract: Certain aspects of the present disclosure provide techniques for handling crash events in a software application using application-agnostic machine learning models. An example method generally includes receiving a data set of crash reports from a software application for analysis. Using a first neural network, a representation of each respective crash report in the data set is generated. The data set of crash reports and a mapping between functions in the software application and a multidimensional space are input into the first neural network. Each respective crash report in the data set is classified using a second neural network and the representation of each crash report in the data set. One or more actions are taken with respect to the software application based on the classifying each respective crash report in the data set.

Abstract: There are provided systems and methods for a compute platform for machine leaning model roll-out. A service provider, such as an electronic transaction processor for digital transactions, may provide intelligent decision-making through decision services that execute machine learning models. When deploying or updating machine learning models in these engines and decision services, a model package may include multiple models, each of which may have an execution graph required for model execution. When models are tested from proper execution, the models may have non-performant compute items, such as model variables, that lead to improper execution and/or decision-making. A model deployer may determine and flag these compute items as non-performant and may cause these compute items to be skipped or excluded from execution. Further, the model deployer may utilize a pre-production computing environment to generate the execution graphs for the models prior to deployment or upgrading.

Abstract: In one example, a cloud printing server may include a processor and a memory coupled to the processor. The memory may include a blockchain management component to register an image forming apparatus with a blockchain associated with multiple entities of a blockchain network, create a distributed ledger relating to the blockchain, create a ledger entry including information indicating operational state and configuration data of the image forming apparatus in the distributed ledger, and transmit an instance of the distributed ledger to the multiple entities including the image forming apparatus.

Abstract: A liquid filtration system is provided. The filtration system includes a filter head and a filter cartridge configured to be removably coupled to the filter head. The filter cartridge includes a shell housing and a filter element. The shell housing defines a first housing end, a second housing end, and a housing sidewall extending between the first housing end and the second housing end. The filter element is received within the shell housing and removably coupled to the shell housing. The filter element includes a media pack configured to filter matter from a fluid flowing therethrough and an endcap coupled to an end of the media pack. The endcap comprising a retaining member engaged with the shell housing.

Abstract: A server includes a memory to store instructions, and a processor, coupled to the memory, to execute the instructions to cause the server to receive a wrapper which includes a plurality of items of information. The plurality of items of information are encrypted and pertain to a state of a device which is remotely located from the server, and include at least one item of information regarding a resource or functionality of the device. The processor may execute the instructions to cause the server to decrypt the wrapper including the plurality of items of information, unwrap and de-aggregate the plurality of items of information from the wrapper, and transmit the plurality of items of information to a digital avatar which virtually represents the device to synchronize a state of the digital avatar with the state of the device.

Abstract: There are provided systems and methods for optimizing training data generation from real-time prediction systems for intelligent model training. A service provider, such as an electronic transaction processor for digital transactions, may utilize different computing environment and services that implement machine learning models and engines. The service provider may have a live adjudication environment where models use live data to adjudicate on requests by users, as well as an audit environment where models are trained and tested before deployment. Models may have directed graphs that designate the model dependencies on variables that are processed and values for those variables are used for an output. When variables are shared between models in the adjudication and audit environment, the values for the shared variables may be published to the audit computing environment for use without reloading and processing data, thereby reducing computational load from the audit environment.

Abstract: Systems, methods and computer program code are provided to select a payment gateway for use in a transaction which include receiving information identifying the transaction, identifying a set of available payment gateways, calculating a success probability associated with each payment gateway in the set of available payment gateways, selecting the payment gateway having the highest success probability, and causing the transaction to be processed using the selected payment gateway.

Abstract: This application discusses identifying data processing timeouts in live risk analysis systems. A service provider, such as an electronic transaction processor, may provide a production computing environment that includes a risk analysis system having one or more risk models, which may be machine-learning based. These risk models may be utilized in order to determine whether incoming data processing requests are fraudulent. To test these risk models using production data traffic, an audit computing environment made of a set of machines that do not service production computing environment requests, but that utilize databases and data connections as are used by the production systems. The audit computing environment may thus mirror the risk models and functionality of the production computing environment without the drawbacks of a typical fully separate testing environment.

Abstract: Various implementations described herein are able to leverage the interaction from one or more potential buyers relative to a digital image to automatically create a sales listing for items that appear to be of interest to the buyers. This reduces or eliminates all together the manual effort previously required of sellers in researching and collecting data on each item they wish to sell. Because of their technical nature, the innovative solutions described herein are also readily scalable which, in turn, greatly improves the seller's experience. Based on buyer interaction experiences, sales listings for each item for sale can be automatically created and listed.

Abstract: An additive manufacturing system may include a build platform configured to receive a particulate, a particulate dispenser configured to deposit the particulate onto said build platform, a consolidation device configured to consolidate at least a portion of the particulate to form a component, a first actuator assembly configured to rotate said build platform about a rotation axis at a first speed, and a second actuator assembly configured to rotate said shaft about the rotation axis at a second speed different from the first speed.

Abstract: Various implementations described herein are able to leverage the interaction from one or more potential buyers relative to a digital image to automatically create a sales listing for items that appear to be of interest to the buyers. This reduces or eliminates all together the manual effort previously required of sellers in researching and collecting data on each item they wish to sell. Because of their technical nature, the innovative solutions described herein are also readily scalable which, in turn, greatly improves the seller's experience. Based on buyer interaction experiences, sales listings for each item for sale can be automatically created and listed.

Abstract: A user device may receive, from a server device, a three-dimensional model of a product, and may display the three-dimensional model of the product, with a product review option, in an augmented reality user interface. The user device may display a product feature review panel, product review features, and product feature hotspots, with the three-dimensional model in the augmented reality user interface, based on selection of the product review option. The user device may receive a review of a product feature, via one of the product feature hotspots associated with the product feature and provided in the augmented reality user interface, and may submit the review of the product feature to the server device.

Abstract: In an example, a non-transitory computer readable storage medium may include instructions that when executed cause a computing device to generate a virtual device representation of an image forming apparatus on a cloud. Further, instructions cause the computing device to update the virtual device representation on the cloud with a configuration state of the image forming apparatus. Furthermore, instructions cause the computing device to analyze the updated virtual device representation to determine whether the image forming apparatus is compliant with a stored policy. Further, instructions cause the computing device to initiate, via the virtual device representation, a remediation action to bring the image forming apparatus to compliance based on the determination.

Abstract: There are provided systems and methods for a compute platform for machine leaning model roll-out. A service provider, such as an electronic transaction processor for digital transactions, may provide intelligent decision-making through decision services that execute machine learning models. When deploying or updating machine learning models in these engines and decision services, a model package may include multiple models, each of which may have an execution graph required for model execution. When models are tested from proper execution, the models may have non-performant compute items, such as model variables, that lead to improper execution and/or decision-making. A model deployer may determine and flag these compute items as non-performant and may cause these compute items to be skipped or excluded from execution. Further, the model deployer may utilize a pre-production computing environment to generate the execution graphs for the models prior to deployment or upgrading.

Abstract: Certain aspects of the present disclosure provide techniques for handling crash events in a software application using application-agnostic machine learning models. An example method generally includes receiving a data set of crash reports from a software application for analysis. Using a first neural network, a representation of each respective crash report in the data set is generated. The data set of crash reports and a mapping between functions in the software application and a multidimensional space are input into the first neural network. Each respective crash report in the data set is classified using a second neural network and the representation of each crash report in the data set. One or more actions are taken with respect to the software application based on the classifying each respective crash report in the data set.

Abstract: A new adhesive composition comprising a cycloaliphatic-based epoxy composition, which is particularly suitable for use as a structural adhesive in anchoring applications.

Abstract: Techniques are disclosed for time constrained electronic request evaluation. A server system receives, from a computing device, a request submitted via an account, including a first set of characteristics associated with the request. The system executes a first machine-learning model to determine a first risk score for the request by inputting the first set of characteristics into the first model. The system generates an initial authentication decision for the request based on the first score and sends the decision to the device. The system executes a second, different machine-learning model to determine a second risk score for the request, by inputting the first set of characteristics and a second, different set of characteristics associated with the account into the second model. Based on the second score, the system determines a final authentication decision. The disclosed techniques may advantageously improve computer security and operations via identification of malicious electronic requests.

Abstract: The invention relates to a front underrun protection device for a heavy vehicle comprising a beam configured to extend from side to side of the vehicle at a lower front position thereof and to absorb collision energy. The beam is at least partly made of a plastic or polymeric material. The beam comprises a housing beam member having at least one channel extending along the housing beam member, and at least one reinforcement beam member adapted to fit into the channel of the housing beam member. The reinforcement beam member is arranged in the channel and arranged to extend along the housing beam member. The reinforcement beam member is provided with a plurality of wall elements comprising transversal wall elements distributed along and extending across the reinforcement beam member and longitudinal wall elements extending in a longitudinal direction of the reinforcement beam member between the transversal wall elements.