Abstract: Conventional techniques implemented various explicit rules and engineer systems to deliver a solution. Stores and Distribution Centers (DC's) are faced with problems related to excess inventory/lack of inventory which vary with several, and the biggest challenge lies in matching supply with demand. Present disclosure provides systems and methods that perform node ranging wherein range of items are stocked in stores and DCs for fulfilling demand. The system identifies stores and DCs and further recommend store specific items based on a request received by the system and then implements a supervised machine learning model and a reinforcement learning models determine a range of items to be sized from the recommended store specific items which are based on most frequent line items being identified from a set of inputs received therein.

Abstract: The embodiments of present disclosure herein address unresolved problems in existing initiatives to optimize costs and streamline the return decisions which are based on legacy infrastructure and explicit rules such as a SQL database. Embodiments herein provide a method and system for streamlining return decision in a supply chain network and optimizing costs. The system is configured to create a returns decision environment using an OpenAI gym base class. Created classes lend extensibility for Reinforcement Learning (RL) applications through a supply chain management environment base class and more specific returns decision environment class. These encapsulate all of the environment functions including exploration of contextual information in the dataset.

Abstract: Disclosed herein are system, method, and computer program product embodiments for generating a set of correlated applications by a recommendation system to resolve an incident for an application service (AS). The recommendation system can determine an AS-to-AS similarity matrix based on incident data and contextual data, an AS-to-AS affinity matrix based on the incident data and contextual data, and generate a set of correlated applications based on the similarity matrix and the affinity matrix. The set of correlated applications can also be generated based on pairwise application associations, where an application association between a first application and a second application indicates that the first application and the second application can occur together in an incident or to be changed together as indicated by a change record.

Abstract: Methods, systems, and devices for data management are described. A data management system may support techniques for bulk object selection and recovery for a set of computing objects. The data management system may receive an indication of a backup snapshot group identifier which defines a selection of a group of backup snapshots for performing a bulk recovery. The backup snapshot group identifier is then translated into a materialized list of object identifiers corresponding to the set of backup snapshots for storage in a binary large object (BLOB) data store. The data management system may then perform the bulk recovery on a subset of the set of backup snapshots contained within a sliding window that is iterated through the list of object identifiers within the BLOB data store.

Abstract: Leveraging a large language model (‘LLM’) for managing a fleet of storage systems, including: receiving, by a fleet management service, data describing states of a plurality of storage systems in a fleet of storage systems; requesting, by the fleet management service and from a large language model (LLM), a fleet management recommendation based on the data; and receiving, by the fleet management service and from the LLM, a fleet management recommendation for the fleet of storage systems.

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: Generally described, the presently disclosed technology utilizes managed Wi-Fi networks pre-installed throughout an MDU property to provide user-specific passphrases that can be used to access the single-SSID wireless network at the property and to provide a cloud portal that can enable convenient access to the functionalities (both by the resident and the manager) provided by the Wi-Fi controller and the Wi-Fi access points. By doing so, the Wi-Fi network management solutions described herein allow the users to experience the benefits of a shared Wi-Fi infrastructure, such as not having to set up and maintain their own Wi-Fi routers, while also allowing them to easily change their Wi-Fi settings from their connected devices.

Abstract: A data platform for providing large scale data discovery with near real time data cataloguing and detailed lineage. Data is received from one or more sources, and the received data is written to a data storage systems. The received data is processed at the data storage systems using sensors at the data storage systems. Metadata and data definitions associated with the data are sent to a data service in near real-time. A data catalog is generated at the data service based on the metadata and data definitions associated with the data. Data lineage for the data is created at the data service. The data catalog and data lineage are presented at a data discovery interface.

Abstract: Separator and electrolyte composites include a porous self-supporting separator film between or adjacent one or two electrolyte films. The electrolyte films may contain a glyme or mixture of glymes, LiX salt and complexing agent, such as PEO. The porous self-supporting separator film may be used dry or wetted with a liquid electrolyte composition. Solid state batteries and electrochemical cells are disclosed that include the described separator and electrolyte composites in combination with an anode and a cathode.

Abstract: Systems and methods involving provision of machine-learning-based prediction of future failure, anomaly, etc. in execution of batch processes are disclosed. In one illustrative implementation, an exemplary method may comprise obtaining historical data from prior execution of one or more batch processes, training a machine learning model to predict one or more future failure(s) and/or future flag(s) in execution of a future batch process, generating and/or collecting descriptive analytics pertinent to execution of the batch processes, and predicting a future failure and/or future flag in execution of the batch processes using the trained machine learning model and/or the descriptive analytics.

Abstract: A system comprises a first data center, a second data center and a cloud server. A first server of the first data center receives a command to process a first processing job, accesses from the cloud server a software application, and processes the first processing job using the software application. The first server transmits the processing data associated with the processing to a second data center. A second server of the second data center receives and stores the processing data in a memory associated with the second data center. The second server detects that the processing of the first processing job was interrupted at the first server and, in response, resumes the processing based on the processing data.

Abstract: Generally described, the presently disclosed technology utilizes managed Wi-Fi networks pre-installed throughout an MDU property to provide user-specific passphrases that can be used to access the single-SSID wireless network at the property and to provide a cloud portal that can enable convenient access to the functionalities (both by the resident and the manager) provided by the Wi-Fi controller and the Wi-Fi access points. By doing so, the Wi-Fi network management solutions described herein allow the users to experience the benefits of a shared Wi-Fi infrastructure, such as not having to set up and maintain their own Wi-Fi routers, while also allowing them to easily change their Wi-Fi settings from their connected devices.

Abstract: In a network host discovers each node n and each audio group at each node, an audio group including audio channel(s) and being one of a source or a sink. The host receives identification of at least one audio stream having a source audio group and sink audio group(s). The host derives, for each node n starting from main downstream to a last node: register values DNMaskReg(n) and register values DNSlotReg(n). The host derives, for node n starting from the last node and proceeding to the main node: register values UPMaskReg(n) and UPSlotReg(n). The host derives, for each node n: register values TXCrossReg(n) and RXMaskReg(n). The host writes, over the network to a corresponding register of each node n, the derived register values.

Abstract: The present invention relates to a system and a method for managing communication between at least one NB-IoT device and an application server. The method comprises continuously receiving, at a mobility management unit, one or more data request from the application server for the at least one NB-IoT device. The mobility management unit transmits a paging request to the at least one NB-IoT device and dynamically monitors a response to the paging request from the at least one NB-IoT device. The mobility management unit continuously buffers the one or more data request based on the dynamic monitoring, and transmits, the one or more buffered data request based on one of an expiry of the paging request and the dynamic monitoring for managing communication between at least one NB-IoT device and the application server.

Abstract: In implementations for free form radius editing, a computing device implements a radius editing system, such as may be integrated with an image editing application. The radius editing system can determine the edge segments for outlines of image objects depicted in a digital image, where the edge segments include corner segments of the image objects. The radius editing system can also determine the radius values of the corner segments of the image objects, and the radius values of the corner segments are maintained in a cache as part of object data corresponding to the image objects depicted in the digital image. The radius editing system can also identify one or more similar corner segments of the image objects that have an equivalent radius value as a selected corner segment responsive to an editing input of a radius of the selected corner segment of an image object.

Abstract: Some embodiments include utilizing a multilink media access control (MAC) address structure to support multilink devices (MLDs) that can operate concurrently in more than one link such as extremely high throughput (EHT) access points (APs) and EHT stations (STA), where the multilink MAC address structure is compatible with legacy devices. An EHT AP can utilize a multilink basic service set (BSS) identification (BSSID) MAC address to communicate with an EHT STA identified by a multilink MAC address. Values of the multilink BSSID and the multilink MAC address of the EHT STA are independent of which of the multiple links are used in the communication. In addition, to utilizing a multilink BSSID, the EHT AP can also support unique link-specific MAC addresses to concurrently support legacy and MLD stations. The EHT STA can also utilize unique link-specific MAC addresses that can be different than the EHT AP's link-specific MAC addresses.

Abstract: State of art techniques supply chain management system tend to mostly focus on end to end supply chain management and lose focus on the port of dispatch to retailer segment of supply chain. A method and system for demand driven, constraint-based and cost optimized inbound container prioritization for resilient supply chain is disclosed. Current demand, multiple constraints across destination port, transport carriers, distribution centers, external factors, looks at multiple supply chain cost components like free days, demurrage, transportation, manpower is considered and a ‘n’ week rolling dynamically prioritized list of inbound containers, is generated, which needs to be picked up from the destination port for addressing the volatile customer demand. The dynamic prioritization uses an intelligent ranking algorithm that calculates an urgency score for each container based on crucial parameters before creating a pickup list and helps in maximizing profit while reducing logistic overheads for the retailer.

Abstract: A method for workload-driven index selections includes receiving a request for a recommended index configuration. The method includes obtaining a plurality of queries executed at the database. The method also includes selecting a set of candidate indexes from the plurality of indexes. The method includes for each respective candidate index of the set of candidate indexes, determining, based on the plurality of queries, a respective workload cost for the respective candidate index. The method also includes selecting, based on the respective workload cost, a first candidate index from the set of candidate indexes for the recommended index configuration. The method includes selecting one or more additional candidate indexes from the set of candidate indexes for the recommended index configuration. The method includes determining that a size of the selected candidate indexes satisfies a size threshold and transmitting the recommended index configuration.

Abstract: Systems, computer program products, and methods are described herein for determining and applying a backup file attribution to files in an electronic network. The present invention is configured to receive data associated with at least one file, wherein the file is stored in at least one data store; and generate at least one file attribute for the file, wherein, in an instance where the file is a tape file type, generate a backup file attribute, wherein, in an instance where the file is not a tape file type, generate a non-backup file attribute, wherein, in an instance where the file is not a type file type and the file comprises a backup feature in the data, generate the backup file attribute, or wherein, in an instance where the file is a tape file type and the file comprises a non-backup feature in the data, generate the non-backup file attribute.

Abstract: Systems and methods involving provision of machine-learning-based prediction of future failure, anomaly, etc. in execution of batch processes are disclosed. In one illustrative implementation, an exemplary method may comprise obtaining historical data from prior execution of one or more batch processes, training a machine learning model to predict one or more future failure(s) and/or future flag(s) in execution of a future batch process, generating and/or collecting descriptive analytics pertinent to execution of the batch processes, and predicting a future failure and/or future flag in execution of the batch processes using the trained machine learning model and/or the descriptive analytics.