Abstract: Systems, methods, and computer program products that use unsupervised learning to learn relationships between operations of a machine learning model based on a model graph representation to group the operations into clusters and, given a set of clusters and labels for the clusters, use a reinforcement learning algorithm to generate a final device placement result for the machine learning model.

Abstract: A display panel and a display device are provided. An organic light-emitting layer includes a doped region and an undoped region, and the undoped region is located between the doped region and the hole blocking layer. When the display panel is in a low grayscale display state, an exciton concentration distribution curve of the organic light-emitting layer includes a first peak located in the doped region and a second peak located in the undoped region, and a peak value of the second peak is less than a peak value of the first peak.

Abstract: A plurality of wireless charging systems may be employed within a network at a venue or other physical area to precisely locate a battery-operated node of the network. The location of the node may then be used to manage a transaction between that node and another node within the network when the transaction is associated with that precise location.

Abstract: A system and method for 1) storing, in data stores, data associated with tenants in separated regions, each region corresponding to a tenant; 2) receiving a request from a first tenant to share data associated with the first tenant with other tenants; 3) storing, based on the request, access control data identifying data associated with the first tenant that is subject to sharing with the other tenants; 4) accessing model building data from the tenanted database system, the model building data defined at least in part by the access control data, wherein the model building data is associated with the first tenant and the other tenants; 5) creating a model based on the data associated with the first tenant and, if applicable, other data associated with the other tenants; and 6) providing access to the model to one or more other tenants.

Abstract: Embodiments of the present disclosure disclose display panels and display devices. The display panel includes a substrate, a pixel definition layer, a light emitting layer, and partitions. The pixel definition layer includes first grooves and second grooves arranged in a non-light emitting area. Each partition includes a first portion and a second portion connected to each other. The first portion corresponds to the second groove. A width of the second portion is greater than a width of the first portion. The second portion is spaced apart from a surface of the pixel definition layer away from the substrate.

Abstract: False data entities attempt to evade getting caught by changing their information repeatedly over time. Systems and methods are provided to detect false data entities. A computing system ingests a plurality of data files respectively from a plurality of external data sources using the network interface within a current specified time period. It consolidates a plurality of data entries of false data entities from the plurality of data files into a consolidated list for the current specified time period. It compares the consolidated list for the current specified time period with a previous consolidated list corresponding to a previous specified time period to identify one or more differences. It then updates a database, which comprises a current list of false data entities, with the one or more differences.

Abstract: A method for dynamically assigning an inference request is disclosed. A method for dynamically assigning an inference request may include determining at least one model to process an inference request on a plurality of computing platforms, the plurality of computing platforms including at least one Central Processing Unit (CPU) and at least one Graphics Processing Unit (GPU), obtaining, with at least one processor, profile information of the at least one model, the profile information including measured characteristics of the at least one model, dynamically determining a selected computing platform from between the at least one CPU and the at least one GPU for responding to the inference request based on an optimized objective associated with a status of the computing platform and the profile information, and routing, with at least one processor, the inference request to the selected computing platform. A system and computer program product are also disclosed.

Abstract: A supporter of lithium metal, a material of the supporter of lithium metal is at least one of copper, an alloy of the copper, nickel, or an alloy of the nickel, and a surface of the supporter of lithium metal comprises a lithiophilic surface.

Abstract: Systems, methods, and computer program products are provided for dynamically processing model inference or training requests. A system may include at least one processor to receive a plurality of requests from a plurality of requesting systems, create a plurality of instantiations of at least one machine-learning model based on the plurality of requests and service data associated with each requesting system of the plurality of requesting systems, stream data associated with at least one request of the plurality of requests to each instantiation of the plurality of instantiations, adjust a rate limit for each instantiation of the plurality of instantiations based on the service data associated with at least one requesting system related to a respective instantiation, resulting in an adjusted rate limit, and process at least one request of the plurality of requests with an instantiation of the plurality of instantiations based on the adjusted rate limit.

Abstract: Embodiments of the present disclosure provide a display panel comprising a light-emitting element, in which the light-emitting element includes a first electrode layer, a first light-emitting layer, a first buffer layer, a first charge-generating layer, a second buffer layer, a second light-emitting layer, and a second electrode layer; in which the first charge-generating layer includes a first n-type charge-generating layer and a first p-type charge-generating layer, and both of the electron mobility of the first buffer layer and the electron mobility of the second buffer layer are less than the electron mobility of the first n-type charge-generating layer.

Abstract: Provided are a method and system for interactively searching for a target object and a storage medium. The method includes: obtaining a first interactive instruction from a first terminal; determining a target object corresponding to the first interactive instruction; obtaining target information of the target object; where the target information includes at least one of: a current position of the target object, picture information of the current position, a historical trajectory of the target object, a navigation route, or any combination thereof; sending the target information to the first terminal such that the first terminal displays the target information.

Abstract: Embodiments of the present disclosure are directed to onboarding a model from a training platform to an inference platform and selecting parameters of the model to optimize performance of the model. For example, the onboarding of the model to the inference platform can be based on a series of interactions between a model onboarding systems at the training platform and at the inference platform. An optimization process can include a searching-based process to derive optimal settings for the model. The optimization process can simulate feature combinations of the model and identify an optimal combination of settings of the model for increased model performance.

Abstract: Provided herein are systems and methods for tissue characterization that may be utilized for intraoperative cancer margin assessment. A tissue sample is resected from a patient and then placed in a system where it is imaged for autofluorescence characteristics to help identify regions of interest such as cancerous tissue margins. Based on the imaging results and tissue characterization, the resection of tissue in the subject can be adjusted.

Abstract: The present disclosure provides a pedestrian tracking method including: acquiring at least one piece of first video data and at least one piece of second video data; performing facial recognition on at least some first images of the first image frames to obtain tracking data of a first pedestrian including position information thereof at N moments; performing human body detection on at least some second images of the second image frames to obtain tracking data of a second pedestrian including a movement track thereof; determining tracking data of a target pedestrian when deviation between the position information of the first pedestrian at the N moments and the position information of the movement track of the second pedestrian at the same moments is within a preset range. The present disclosure also relates to a pedestrian tracking apparatus, a computing device, a pedestrian tracking system, and a computer-readable storage medium.

Abstract: A hydrogen production system and a method for controlling the same are provided. A renewable energy power generation system supplies electric energy to a hydrogen production device. The hydrogen production device discharges acceptable-purity hydrogen to the main hydrogen branch and discharges unacceptable-purity hydrogen to the mixed hydrogen branch. The mixed hydrogen branch receives high-purity hydrogen. The mixed hydrogen branch includes two valves to respectively control volumes of the high-purity hydrogen and the unacceptable-purity hydrogen flowing into the hydrogen mixing device in the mixed hydrogen branch, to control mixed hydrogen in the hydrogen mixing device to be the acceptable-purity hydrogen. The acceptable-purity hydrogen in the hydrogen mixing device is discharged to a purification branch in the main hydrogen branch, or a purification branch in the mixed hydrogen branch.

Abstract: A method for dynamically assigning an inference request is disclosed. A method for dynamically assigning an inference request may include determining at least one model to process an inference request on a plurality of computing platforms, the plurality of computing platforms including at least one Central Processing Unit (CPU) and at least one Graphics Processing Unit (GPU), obtaining, with at least one processor, profile information of the at least one model, the profile information including measured characteristics of the at least one model, dynamically determining a selected computing platform from between the at least one CPU and the at least one GPU for responding to the inference request based on an optimized objective associated with a status of the computing platform and the profile information, and routing, with at least one processor, the inference request to the selected computing platform. A system and computer program product are also disclosed.

Abstract: A system includes an interface and a processor. The interface is configured to receive a request to access shared services; provide a user interface for selecting a shared service of the shared services; and receive a selection of the shared service of the shared services. The processor is configured to determine data associated with the shared service of the shared services; store a shared-service tag indicating the data is associated with the shared service of the shared services and an identifier tag indicating the data is associated with a source; transfer the data to a model development system; determine a model using the data transferred to the model development system; and store the model.

Abstract: A method may include obtaining feature data associated with a set of feature inputs of a machine learning model, determining a probability that a subset of the feature data is concurrently used as the set of feature inputs for the machine learning model, and storing the subset of the feature data on a same cache node or server of a plurality of cache nodes or servers based on the probability.

Abstract: A real-time geo-intelligent aggregation engine and related methods are disclosed. The real-time geo-intelligent aggregation engine can be used to provide interaction event data corresponding to a geographic coordinate point and a boundary element to requestors or requestor computers. After receiving a request from a requestor computer, the real-time geo-intelligent aggregation engine can determine one or more geohashes corresponding to a geographic region. The one or more geohashes can be used to query a geographic resource provider database to determine a list of resource providers acting within the geographic region. The list of resource providers can be used to query a resource provider interaction database to determine interaction event data corresponding to those resource providers. The interaction event data can subsequently be provided to the requestor computer.

Abstract: A system and method for 1) storing, in data stores, data associated with tenants in separated regions, each region corresponding to a tenant; 2) receiving a request from a first tenant to share data associated with the first tenant with other tenants; 3) storing, based on the request, access control data identifying data associated with the first tenant that is subject to sharing with the other tenants; 4) accessing model building data from the tenanted database system, the model building data defined at least in part by the access control data, wherein the model building data is associated with the first tenant and the other tenants; 5) creating a model based on the data associated with the first tenant and, if applicable, other data associated with the other tenants; and 6) providing access to the model to one or more other tenants.