Abstract: Aspects described herein may utilize self-federation in a plugin-based authentication system to support combinations of authentication processes. The authentication system may include a plugin that executes an authentication process that is a combination of two or more other authentication processes. This plugin may handle the combined authentication process by self-federating back to the authentication interface, generating its own authentication requests under each of the subsidiary authentication processes. Thus, the self-federating plugin corresponding to the combined authentication process may allow the authentication system to support authentication requests that indicate the combined authentication process. This “chained” authentication process, accomplished through self-federation, may allow the authentication system to reuse existing code paths and avoid downsides associated with duplication of code.

Abstract: In some embodiments, a computer-implemented method includes ascertaining a multitier topology representation of an edge cloud network; generating a pseudo node topology representation of the edge cloud network from the multitier topology representation; and utilizing the pseudo node topology representation of the edge cloud network to ascertain minimum-latency pseudo-node-based edge cloud clusters (ECCs), the minimum-latency pseudo-node-based ECCs being utilized to minimize a latency of user requests routed through the edge cloud network from a user of the edge cloud network. In some embodiments of the computer-implemented method, the minimum-latency pseudo-node-based ECCs are ascertained based upon a pseudo-node-based round-trip-times (RTTs) assessment from the user of the edge cloud network, the user requests being routed to the minimum-latency pseudo-node-based ECCs ascertained using the pseudo node topology representation.

Abstract: A Scope 3 emission system includes a controller with a microprocessor and a memory. The memory stores executable instructions that when executed by the microprocessor cause the microprocessor to perform a computer-executable method. The method comprises generating embeddings based on enterprise financial transaction data, enterprise metadata, and crowd source data, and generating sector wise carbon-aware spatio-temporal weights indicative of an estimated level of Scope 3 emissions produced by a corresponding commodity sector. The method further includes generating a carbon-aware natural language processing (NLP) foundation model (FM) based on the embeddings and the sector wise carbon-aware spatio-temporal weights. User-generated data indicating at least one target commodity sector and spend data associated with the target commodity sector is input into the NLP FM, and the NLP FM outputs an estimation of the Scope 3 emissions based on the least one target commodity sector and the spend data.

Abstract: A data platform provides central data governance and access control for enterprise data. Information identifying data of interest at a storage system is received from users. An Access Request for the data of interest at the storage system is generated. the Access Request is forward to a Data Access Layer of a Data Governance and access Control Layer. An Approval Request is automatically forwarded by the Data Access Layer to one or more access control entities. The Data Access Layer receives an Approval Response from the one or more access control entities. A policy for accessing the data of interest at the storage system is created. The policy is used to provide access to the data of interest at the storage system. The Data Access Layer is also able to provide cross-platform access to different storage sources.

Abstract: Systems, computer-implemented methods, and/or computer program products are provided that facilitate integrating sustainability solutions into an organization's existing business model using artificial intelligence. A computer-implemented method comprises extracting, by a system comprising a processor, one or more objective functions of an enterprise system from defined business model data for the enterprise system, the one or more objective functions defining relationships between one or more processes of the enterprise system and one or more business objectives of the enterprise system.

Abstract: Systems and methods for diagnostic visual search can include processing a search query with a plurality of classification models to determine a search query intent and predict potential diagnosis. The search query can include an image that is processed to determine the presence of a body part and may be processed to determine if the search query is descriptive of a diagnostic search query. Based on the intent determination, the image may then be processed by a conditions classification model to determine one or more predicted condition classifications. Condition information can then be obtained and provided based on the one or more predicted condition classifications.

Abstract: A computer implemented method identifies a set of environmental projects. A number of processor units identifies a group in a plurality of groups for organization of interest using organization parameters for the organization of interest. The number of processor units determines environmental performance for the organizations in the group using environmental data and the organization parameters for the organizations in the group. The number of processor units identifies the set of environmental projects for the organization of interest based on the environmental performance determined for the organizations in the group.

Abstract: The present disclosure is directed to a deep learning system for differential diagnoses of skin diseases. In particular, the system performs a method that can include obtaining a plurality of images that respectively depict a portion of a patient's skin. The method can include determining, using a machine-learned skin condition classification model, a plurality of embeddings respectively for the plurality of images. The method can include combining the plurality of embeddings to obtain a unified representation associated with the portion of the patient's skin. The method can include determining, using the machine-learned skin condition classification model, a skin condition classification for the portion of the patients skin, the skin condition classification produced by the machine-learned skin condition classification model by processing the unified representation, wherein the skin condition classification identifies one or more skin conditions selected from a plurality of potential skin conditions.

Abstract: A method performed by a managing server includes: receiving, from an electronic device, operation data of the electronic device; identifying, by using artificial intelligence (AI), a device usage pattern of the electronic device; identifying, by using the AI, information related to a failure or an abnormal operation of the electronic device and a solution to the failure or the abnormal operation based on the device usage pattern and the operation data received from the electronic device; and transmitting, to a user terminal, the information related to the failure or the abnormal operation of the electronic device and the solution to the failure or the abnormal operation.

Abstract: A method performed by a managing server includes: receiving, from an electronic device, operation data of the electronic device; identifying, by using artificial intelligence (AI), a device usage pattern of the electronic device; identifying, by using the AI, information related to a failure or an abnormal operation of the electronic device and a solution to the failure or the abnormal operation based on the device usage pattern and the operation data received from the electronic device; and transmitting, to a user terminal, the information related to the failure or the abnormal operation of the electronic device and the solution to the failure or the abnormal operation.

Abstract: A method performed by a managing server includes: receiving, from an electronic device, operation data of the electronic device; identifying, by using artificial intelligence (AI), a device usage pattern of the electronic device; identifying, by using the AI, information related to a failure or an abnormal operation of the electronic device and a solution to the failure or the abnormal operation based on the device usage pattern and the operation data received from the electronic device; and transmitting, to a user terminal, the information related to the failure or the abnormal operation of the electronic device and the solution to the failure or the abnormal operation.

Abstract: At least some embodiments are directed to an exemplary computer-based electronic activity tracking system that detects activity patterns receiving data values that represent at least one electronic activity. The exemplary electronic activity tracking system includes a detector of unsecure electronic activities that identifies electronic activity patterns performed by a user or non-person entity. The detector of unsecure electronic activities utilizes unsupervised machine learning techniques to detect the electronic activity patterns. The detected electronic activity patterns correspond to unsecure or malicious electronic activities. The electronic activity tracking system outputs notifications indicative of identified unsecure or malicious activity patterns and identifies entities associated with such unsecure or malicious activity patterns. The exemplary electronic activity tracking system implements a graphical user interface operated from a client computing device.

Abstract: Methods and systems for routing a user request for a service to a version of the service in a geographical region associated with the user are described herein. The service may be deployed in multiple geographical regions, and the service may have multiple versions in each of the geographical regions. A user device may send a request for a service to a first server in a geographical region. The first server may determine whether the user is associated with the geographical region. Responsive to determining that the user is not associated with the geographical region, the first server may ask one or more servers in other geographical regions whether the user is associated with any of the other geographical regions.

Abstract: Systems and methods applicable to generating management decisions for online advertising. Machine learning models, including reinforcement learning-based machine learning models, can be utilized in making various advertising management decisions.

Abstract: Media is streamed in accordance with carbon footprint considerations. A streaming history of a streaming plan is analyzed to determine a historical carbon footprint. At least one streaming plan is presented that includes target carbon footprint relative to the historical carbon footprint. A selection is received for one of the at least one streaming plan, wherein the streaming performance on the streaming plan is tracked for post streaming plan carbon emissions. The user streaming performance is modified for the post streaming plan carbon emissions to substantially match the target carbon footprint of the at least one streaming plan.

Abstract: A system and method for visualizing and querying high dimensional data to a user. The system includes a user device, a data-pearls visualization and querying server. The server obtains the high dimensional data from the user device associated with user. The server generates data clusters and sub-divides the data clusters into non-overlapping subsets of data-pearls using a clustering technique. The server selects a shape for each data-pearl by comparing a distance between centroid of a data-pearl and a farthest point from a determined centroid using Lp norm distance measures. The server configures each data-pearl in a three-dimensional plot. The server enables the user to visualize the data-pearls on a screen of the user device. The server queries data based on a query using data dimension technique. The server dimensions data related to the query through determined classifiers based on filtered data after pruning unrelated data to the query.

Abstract: Methods, systems, computer-readable media, and apparatuses may provide creation and management of composite tokens for use with services in a virtual environment without the user having to re-authenticate each time the user accesses a different service. A composite identity server may receive a request to upgrade a first authentication token for a user. The composite identity server may redirect a user agent to an identity provider for authentication and, in response, may receive a second authentication token for the user. The composite identity server may send the second authentication token to a federated microservice and, in response, may receive one or more claims of the second authentication token designated for inclusion in a composite token. The composite identity server may generate a composite token including the one or more claims of the first authentication token and one or more claims of the second authentication token.

Abstract: Described herein are systems and methods for managing releases of global services in a controlled manner. A computing environment may include a first release of a global service, a second release of the global service, and a manager service. The first and second release may be enabled and disabled. The first release may be enabled and the second release may be disabled. The second release may be ready for use in the computing environment after passing one or more checks. A manager service may enable use of the second release in the computing environment. The manager service may disable use of (but maintain execution of) the first release in the computing environment. The second release may be determined to have one or more issues. Responsive to determining the second release has issue(s), the manager service may disable use of the second release and re-enable use of the first release.

Abstract: The present disclosure is directed to a deep learning system for differential diagnoses of skin diseases. In particular, the system performs a method that can include obtaining a plurality of images that respectively depict a portion of a patient's skin. The method can include determining, using a machine-learned skin condition classification model, a plurality of embeddings respectively for the plurality of images. The method can include combining the plurality of embeddings to obtain a unified representation associated with the portion of the patient's skin. The method can include determining, using the machine-learned skin condition classification model, a skin condition classification for the portion of the patients skin, the skin condition classification produced by the machine-learned skin condition classification model by processing the unified representation, wherein the skin condition classification identifies one or more skin conditions selected from a plurality of potential skin conditions.

Abstract: Described herein are systems and methods for managing releases of global services in a controlled manner. A computing environment may include a first release of a global service, a second release of the global service, and a manager service. The first and second release may be enabled and disabled. The first release may be enabled and the second release may be disabled. The second release may be ready for use in the computing environment after passing one or more checks. A manager service may enable use of the second release in the computing environment. The manager service may disable use of (but maintain execution of) the first release in the computing environment. The second release may be determined to have one or more issues. Responsive to determining the second release has issue(s), the manager service may disable use of the second release and re-enable use of the first release.