Abstract: In an approach for an indoor survey data collection, a processor generates reference points based on a site map and an accuracy requirement. A processor collects data at each reference point through a data collecting agent. A processor detects an outlier at the reference points using a feedback from the data collecting agent during the data collection and a database. A processor eliminates the detected outlier and rectifies the data.

Abstract: A KUBERNETES installation processes a script and invokes a scheduling agent in response to encountering an instruction to create a pod. The scheduling agent is an agent of an orchestrator and performs tasks such as identifying a selected node, creating multiple interface objects with multiple IP addresses, and creating storage volumes in coordination with the orchestrator. Upon creation, the pod may call a CNI that is an agent of the orchestrator in order to configure the pod to use the multiple interface objects. The pod may call a CSI that is an agent of the orchestrator in order to bind a storage volume to the pod. The scheduling agent may coordinate with the orchestrator to implement affinity and anti-affinity rules for placement of pods and storage volumes. The script may also be transformed by the orchestrator in order to insert instructions implementing affinity and ant-affinity rules.

Abstract: Examples include receiving, from a VoIP server, identification information of the virtual meeting and information of a plurality of client devices participating in the virtual meeting, associating each client device of the plurality of client devices to a network device in a set of network devices based on the identification information of the virtual meeting and capabilities of the set of network devices, and creating a proxy agent in each network device in the set. The proxy agent is configured to receive, from the VoIP server, VoIP streaming data of the virtual meeting. Additionally, examples include, configuring the proxy agent to replicate and transmit the VoIP streaming data to the plurality of client devices.

Abstract: Embodiments disclosed herein provide for systems and methods for secure logins using facial recognition with a blockchain-based verification system. The systems and methods provide for authentication, authorization, and secure storage of biometrics data. Authentication is performed with a machine learning system implementing the facial recognition. The biometrics data can be securely stored on a blockchain and used to perform the facial recognition during login. Authorization is provided with an active directory system.

Abstract: The present disclosure is directed to systems and methods for reducing display image power consumption while maintaining a consistent, objectively measurable, level of image distortion that comports with a display image quality metric. Raw image data is converted to an HSV format. “V” values are extracted from the HSV format raw image data and a histogram generates a plurality of “V” values. HSV format raw image data is provided to at least one layer of a trained CNN to extract a plurality of features. The plurality of “V” values and the plurality of features are provided to an AI circuit to generate a plurality of distortion class value pairs. Each of the distortion class value pairs is weighted based on proximity of display image distortion and the display image quality metric. The distortion class pair providing a display image distortion close to the display image quality metric is applied to the raw image data to generate the display image data.

Abstract: Methods, apparatus, systems, and articles of manufacture to control an aggressiveness of display panel power savings are disclosed. An example apparatus include a display panel, a display controller to adjust an image to be displayed by the display panel, and a power savings controller to access an image provided to the display controller, execute a machine learning model using the image as an input to generate an aggressiveness value, and provide the aggressiveness value to the display controller, the display controller to adjust the image based on the aggressiveness value.

Abstract: An embodiment of the present invention is directed to developing Autonomous Fraud Risk Management to identify emerging fraud trends in near real-time and mitigate risk by executing strategies to address fraud in a timely manner.

Abstract: Methods, systems, and devices for wireless communications are described. In some systems, a first device may transmit a signal to a second device including a number of error detection bits interleaved with a number of information bits. The second device may use the error detection bits to determine if the signal was received correctly, where each error detection bit may be associated with a set of information bits. The second device may progressively decode the signal and continuously perform an error detection calculation based on a first set of information bits associated with a first error detection bit. Based on the error detection calculation, the second device may calculate an expected error detection bit corresponding to the first error detection bit. The second device may compare the first error detection bit to the expected error detection bit. Other aspects and features are also claimed and described.

Abstract: Described are mechanisms and methods for applying Machine Learning (ML) techniques for power management at different levels of a power management stack. An apparatus may comprise a first circuitry, a second circuitry, and a third circuitry. The first circuitry may have a plurality of memory registers. The second circuitry may be operable to establish values for a plurality of features based on samples of values of the plurality of memory registers taken at one or more times within a range of time of predetermined length. The third circuitry may be operable to compare the plurality of features against a plurality of learned parameters for a reference workload.

Abstract: One embodiment provides a method, including: receiving a client fashion catalog comprising a plurality of images of client wearable products; creating a market fashion catalog comprising a plurality of market wearable products identified from sources other than the client fashion catalog, wherein the creating comprises (i) accessing a plurality of secondary sources, (ii) capturing information corresponding to market wearable products from the plurality of secondary sources, and (iii) aggregating the information to create the market fashion catalog; generating, for each market wearable product, (iv) a desirability score and (v) a multi-modal description of characteristics; producing, for the market wearable products, by utilizing the multi-modal descriptions, a similarity score indicating how similar the market wearable product is to products within the client fashion catalog, wherein the producing comprises comparing market wearable products to client wearable products; and providing a recommendation for a ch

Abstract: Methods, systems, and computer program products for data filtering with fuzzy attribute association are provided herein. A computer-implemented method includes obtaining one or more rules, specified by an expert, that define a partial ranking of a plurality of fuzzy pairings between (i) a plurality of item attributes for items in a data catalog and (ii) a plurality of user attributes related to said items; generating an interactive session with the expert to resolve one or more ambiguities in the one or more rules; and deriving a scoring function based at least in part on (i) the one or more rules and (ii) the resolved one or more ambiguities, wherein the scoring function generates a comparative score between any two items of said data catalog for a given one of the users associated with the plurality of attributes.

Abstract: Methods, systems, and devices for wireless communications are described. In some systems, a first device may transmit a signal to a second device including a number of error detection bits interleaved with a number of information bits. The second device may use the error detection bits to determine if the signal was received correctly, where each error detection bit may be associated with a set of information bits. The second device may progressively decode the signal and continuously perform an error detection calculation based on a first set of information bits associated with a first error detection bit. Based on the error detection calculation, the second device may calculate an expected error detection bit corresponding to the first error detection bit. The second device may compare the first error detection bit to the expected error detection bit. Other aspects and features are also claimed and described.

Abstract: A new snapshot of a storage volume is created by instructing computing nodes to suppress write requests. Once pending write requests from the computing nodes are completed, storage nodes create a new snapshot for the storage volume by allocating a new segment to the new snapshot and finalizes and performs garbage collection with respect to segments allocated to the previous snapshot. Subsequent write requests to the storage volume are then performed on the segments allocated to the new snapshot. An orchestration layer implements a multi-role application that is provisioned with virtualized storage and computation resources. A snapshot of the application may be created and used to rollback or clone the application. Clone snapshots of storage volumes may be gradually populated with data from prior snapshots to reduce loading on a primary snapshot.

Abstract: A service consumer that utilizes a cloud-based access service provided by a service provider has associated therewith a network that is not capable of being controlled by the service provider. An enterprise connector is supported in this uncontrolled network, preferably as an appliance-based solution. According to this disclosure, the enterprise configures an appliance and then deploys it in the uncontrolled network. To this end, an appliance is required to proceed through a multi-stage approval protocol before it is accepted as a “connector” and is thus enabled for secure communication with the service provider. The multiple stages include a “first contact” (back to the service) stage, an undergoing approval stage, a re-generating identity material stage, and a final approved and configured stage. Unless the appliance passes through these stages, the appliance is not permitted to interact with the service as a connector.

Abstract: One embodiment provides a method, including: receiving a clothing design, wherein the clothing design identifies attributes of an article of clothing; accessing a plurality of information sources having sentiments regarding attributes of pieces of clothing, wherein each of the plurality of information sources is assigned to one of a plurality of geographical regions; identifying location-dependent attributes of the pieces of clothing, wherein the location-dependent attributes comprise clothing attributes whose corresponding user sentiments vary across at least a subset of the geographical regions; and recommending, based upon the location-dependent attributes and a targeted geographical region in which the article of clothing is to be sold, parameter values for the attributes of the article of clothing, wherein the recommending comprises correlating (i) the targeted geographical region with (ii) location-dependent attributes having a positive sentiment within the targeted geographical region.

Abstract: The present disclosure is directed to systems and methods for reducing display image power consumption while maintaining a consistent, objectively measurable, level of image distortion that comports with a display image quality metric. Raw image data is converted to an HSV format. “V” values are extracted from the HSV format raw image data and a histogram generates a plurality of “V” values. HSV format raw image data is provided to at least one layer of a trained CNN to extract a plurality of features. The plurality of “V” values and the plurality of features are provided to an AI circuit to generate a plurality of distortion class value pairs. Each of the distortion class value pairs is weighted based on proximity of display image distortion and the display image quality metric. The distortion class pair providing a display image distortion close to the display image quality metric is applied to the raw image data to generate the display image data.

Abstract: Example display power management control circuitry is to determine a baseline image quality parameter associated with a baseline display power mode based on: a baseline first relationship parameter associated with a first relationship between original and boosted pixel values; a baseline percentage of pixels having a color value; and a baseline second relationship parameter associated with a second relationship between the numbers of original pixel values and boosted pixel values; determine a value of a subsequent first relationship parameter based on an adjusted second relationship parameter and a second percentage of pixels having the color value; determine a second image quality parameter associated with the subsequent first relationship parameter, the adjusted second relationship parameter, and the second percentage of pixels; and select the subsequent first relationship parameter and the adjusted second relationship parameter based on comparing the second image quality parameter to the baseline image qua

Abstract: The present disclosure is directed to systems and methods of optimizing display image quality on display devices having a plurality of display power modes.

Abstract: Described are mechanisms and methods for applying Machine Learning (ML) techniques for power management at different levels of a power management stack. An apparatus may comprise a first circuitry, a second circuitry, and a third circuitry. The first circuitry may have a plurality of memory registers. The second circuitry may be operable to establish values for a plurality of features based on samples of values of the plurality of memory registers taken at one or more times within a range of time of predetermined length. The third circuitry may be operable to compare the plurality of features against a plurality of learned parameters for a reference workload.

Abstract: An advanced security method for verifying that integrated circuit patterns being processed into one or more layers provided to a wafer are trusted patterns and that the wafer being used during processing is a trusted wafer is provided. The method includes separate steps of pattern verification and wafer verification. Notably, the method includes first verifying that a pattern printed on a wafer matches a pattern of a trusted reference. Next, a peak and valley profile present at a specific location on a backside surface of the wafer is measured. The method further includes second verify that the measured peak and valley profile matches an original peak and valley profile measured at the same location on the backside surface of the wafer.