Abstract: A system, method, and computer-readable medium for an information technology (IT) ecosystem management and monitoring operation. The IT ecosystem management and monitoring operation includes: providing a sustainability application to an information handling system, the information handling system comprising a modular component architecture; obtaining sustainability information regarding a component of the information handling system via the sustainability application; providing an IT ecosystem monitoring and management console, the IT ecosystem monitoring and management console comprising an IT ecosystem sustainability system, the IT ecosystem sustainability system comprising a sustainability component; and, communicating between the sustainability component and the sustainability application to perform an IT environment sustainability operation, the communicating providing the sustainability component with the sustainability information regarding the component of the information handling system.

Abstract: Machine assisted systems and methods for enhancing the resolution of an IC thermal profile from a system analysis are described. These systems and methods can use a neural network based predictor, that has been trained to determine a temperature rise across an entire IC. The training of the predictor can include generating a representation of two or more templates identifying different portions of an integrated circuit (IC), each template associated with location parameters to position the template in the IC; performing thermal simulations for each respective template of the IC, each thermal simulation determining an output based on a power pattern of tiles of the respective template, the output indicating a change in temperature of a center tile of the respective template relative to a base temperature of the integrated circuit; and training a neural network.

Abstract: Machine assisted systems and methods for enhancing the resolution of an IC thermal profile from a system analysis are described. The methods can include generating a representation of two or more templates identifying different portions of an integrated circuit (IC); performing a thermal simulation for each respective template of the IC based on a sequence of power patterns of tiles of the respective template; and training a neural network with a plurality of training data collected via thermal simulations performed for the templates of the IC. These systems and methods can use a machine learning predictor, that has been trained to determine a transient temperature rise across an entire IC, and then append the determined transient temperature rise to a system level thermal profile of the IC.

Abstract: A non-reciprocal phase shift device may include an optical waveguide (e.g., a silicon waveguide) on a substrate; and a magneto-optical cladding layer on the optical waveguide, wherein the magneto-optical cladding layer includes a plurality of segments arranged having alternating magnetization directions aligned transverse to a longitudinal direction of the optical waveguide.

Abstract: Machine assisted systems and methods for enhancing the resolution of an IC thermal profile from a system analysis are described. These systems and methods can use a neural network based predictor, that has been trained to determine a temperature rise across an entire IC. The training of the predictor can include generating a representation of two or more templates identifying different portions of an integrated circuit (IC), each template associated with location parameters to position the template in the IC; performing thermal simulations for each respective template of the IC, each thermal simulation determining an output based on a power pattern of tiles of the respective template, the output indicating a change in temperature of a center tile of the respective template relative to a base temperature of the integrated circuit; and training a neural network.

Abstract: Techniques are described herein for presenting attribute variations (differing attribute values) of an item at a network page. A request for the network page associated with an item of an electronic catalog can be received. In response to the request, the network page can be presented. The content and/or format of the network page can be predefined by an interface specification associated with the item and/or item category for the item. The network page may include a first area that includes an expanded view in which one or more variations of the first attribute are depicted and any suitable number of collapsed views in which one or more variations associated with a respective attribute are hidden from view. The areas of the network page may be dynamically expanded and collapsed to enable selection of various attribute values which may then be used to update the network page.

Abstract: A method and system for data synchronization in a multi-tenant data synchronization system is provided.

Abstract: State of art techniques mostly rely of computationally intensive, time consuming Neural Networks. Embodiments provide a method and system for identification and classification of different grain and adulterant types for grain grading analysis. The method analyzes input image of grain sample of elements to determine morphological features of elements, using dynamically determined calibration factor from reference object in the image. Variation in perimeter of elements is used to perform classification of elements into target grain size, low size adulterants and higher size adulterants. The aspect ratio of target grain determines grain variety and adulterants determine adulteration percentage. Elements are classified into grain colored and non-grain colored adulterants. Grain colored adulterants are further classified as Grain Like Impurities and non-GLI, using predefined ranges of standard deviation of perimeter metric.

Abstract: Monitoring of animals in a herd has various challenges. A method and a system for monitoring and measuring the behavior of a plurality of animals in a herd chamber is provided. The disclosure provides a method to develop a model to identify the animal interactions between a given set of herds of two or more animals. The system uses image, RFID sensors, animal phenotyping information such as species, breed, age and reproduction cycle information to generate an animal profile. This profile is used to quantify the interaction into an aggression score to the animals in the given herd. The aggression score over a given duration can help herd manager to put the animals with similar aggression score together. This will also help analyze the temporal aspects of the aggression score for a given animal and take preventive measures.

Abstract: Systems, computer program products, and methods are described herein for authentication decision engine for real-time resource transfer.

Abstract: A method and an apparatus for capturing a high quality dynamic image by setting a different row-wise exposure value when capturing a scene are provided. The dynamic image capturing method includes: generating an image by pre-capturing a scene via an event sensor; generating event data from the image; determining a row-wise exposure value of the image based on the event data; and determining a row-wise readout priority order of the image based on the row-wise exposure value of the image.

Abstract: The present disclosure provides a clustering device configured to detect varying density. The clustering device may receive a set of parameters (e.g., a density parameter specifying a plurality of density values, a size parameter, and a node parameter that includes information associated with a plurality of nodes) for identifying clusters. The clustering device may determine a distance between different pairs of nodes of the plurality of nodes and identify candidate nodes of the plurality of nodes based on the distance determined for the different pairs of nodes and the size parameter. Candidate nodes may be assigned to a candidate cluster that may be evaluated against the density parameter to determine whether a density of the candidate cluster satisfies at least one of the plurality of density values. A cluster may be identified based on whether the candidate cluster satisfies at least one of the plurality of density values.

Abstract: Machine assisted systems and methods for enhancing the resolution of an IC thermal profile from a system analysis are described. These systems and methods can use a neural network based predictor, that has been trained to determine a temperature rise across an entire IC. The training of the predictor can include generating a representation of two or more templates identifying different portions of an integrated circuit (IC), each template associated with location parameters to position the template in the IC; performing thermal simulations for each respective template of the IC, each thermal simulation determining an output based on a power pattern of tiles of the respective template, the output indicating a change in temperature of a center tile of the respective template relative to a base temperature of the integrated circuit; and training a neural network.

Abstract: A method of fabricating a gyrotropic device (e.g., an optical isolator) includes: providing a substrate comprising a waveguide layer and forming an optical isolator active layer on the waveguide layer of the substrate. Forming the optical isolator active layer includes, for a specified composition of the optical isolator active layer, deriving at least one sputtering process parameter, performing sputtering of a plurality of targets according to the at least one sputtering process parameter to deposit the optical isolator active layer on the waveguide layer of the substrate, measuring an initial value of a bias voltage at a first target of the plurality of targets; and throughout deposition of the optical isolator active layer, maintaining the bias voltage at the initial value to within a predetermined threshold of the initial value.

Abstract: Machine assisted systems and methods for enhancing the resolution of an IC thermal profile from a system analysis are described. These systems and methods can use a neural network based predictor, that has been trained to determine a temperature rise across an entire IC. The training of the predictor can include generating a representation of two or more templates identifying different portions of an integrated circuit (IC), each template associated with location parameters to position the template in the IC; performing thermal simulations for each respective template of the IC, each thermal simulation determining an output based on a power pattern of tiles of the respective template, the output indicating a change in temperature of a center tile of the respective template relative to a base temperature of the integrated circuit; and training a neural network.

Abstract: A method for real-time semantic image segmentation using a monocular event-based sensor includes capturing a scene using a red, green, blue (RGB) sensor to obtain a plurality of RGB frames and an event sensor to obtain event data corresponding to each of the plurality of RGB frames, performing object labeling for objects in a first RGB frame among the plurality of RGB frames by identifying one or more object classes, obtaining an event velocity of the scene by fusing the event data corresponding to the first RGB frame and at least one subsequent RGB frame among the plurality of RGB frames, determining whether the event velocity is greater than a predefined threshold, and performing object labeling for objects in the at least one subsequent RGB frame based on the determination.

Abstract: A method and apparatus are provided for performing depth estimation of an object in an image of a scene. The method includes capturing the image of a scene; obtaining, by a sensor, from the image, pixel intensity data and event data; generating an event depth map using the event data, wherein the event data includes event map data of the image and event velocity data of the image; and generating a depth map for the object in the image using the event depth map and the pixel intensity data.

Abstract: The present disclosure provides a clustering device configured to detect varying density. The clustering device may receive a set of parameters (e.g., a density parameter specifying a plurality of density values, a size parameter, and a node parameter that includes information associated with a plurality of nodes) for identifying clusters. The clustering device may determine a distance between different pairs of nodes of the plurality of nodes and identify candidate nodes of the plurality of nodes based on the distance determined for the different pairs of nodes and the size parameter. Candidate nodes may be assigned to a candidate cluster that may be evaluated against the density parameter to determine whether a density of the candidate cluster satisfies at least one of the plurality of density values. A cluster may be identified based on whether the candidate cluster satisfies at least one of the plurality of density values.

Abstract: Systems, computer program products, and methods are described herein for authentication decision engine for real-time resource transfer.

Abstract: A machine learning based recommendation model, including a supervised learning classifier configured to receive input training data that includes a plurality of behavioral determinants, a supervised learning model configured to receive subject input data that includes a plurality of behavior determinants, wherein the supervised learning model outputs a predicted behavior of a subject, and a channel selection module configured to receive the subject input data and the predicted behavior and to determine a recommended communication channel for the subject to follow to achieve the predicted behavior.