Abstract: A system for color gamut normalization for pathology slide is disclosed. The system includes at least a computing device, wherein the computing device is configured to generate a plurality of segmentations of a whole slide image, wherein the whole slide image includes a plurality of biological tissue type variabilities. The computing device is configured to apply a segment-specific transformation to an individual segment in a first region. The computing device is configured to apply the segment-specific transformation to an individual segment in a second region. The computing device is configured to retrieve a plurality of discrete magnification levels from a user. The computing device is configured to choose as a first magnification level from the plurality of discrete magnification levels, and the computing device is configured to store the plurality of segmentations in a cache.

Abstract: An instrument to prepare and safely place an intra-uterine device in uterus of a woman, comprising a dynamic stopper, a string management arrangement whereby a string of an IUD is in one of a locked condition or an unlocked condition, an operating device, further comprising a base, a cover a carriage, wherein the dynamic stopper slidably resides in the base and can slide by the sliding length, wherein the string exits from an outpoint and re-enters from an inpoint, the outpoint is at a trim length and the inpoint is at a conservative length. The string can be trimmed as per sounding measurement of uterus of woman, before inserting the instrument in uterus and string entanglement possibilities are eliminated, irrespective of type of IUD.

Abstract: A data management system may support techniques for immutable storage of snapshot data entities, which may each include data corresponding to one or more snapshots, in a cloud environment. The data management system may determine respective retention periods and respective immutability periods for the snapshot data entities. The data management system may extend the respective immutability period for a first snapshot data entity based on the respective retention period for the first snapshot data entity being greater than or equal to a threshold duration. Additionally or alternatively, the data management system may maintain (refrain from extending) the respective immutability period for a second snapshot data entity based at least in part on the respective retention period for the second snapshot data entity being less than the threshold duration.

Abstract: A catheter system which provides adjustability of the length of the guidewire extending distally from the distal tip of the catheter and/or allows the guidewire to be secured relative to the catheter hub to allow the guidewire and the catheter to be steered simultaneously. The catheter system may include a catheter having an elongate shaft defining a catheter lumen, a hub assembly coupled to the proximal end of the elongate shaft and including a hub assembly lumen, a torque assembly releasably coupled to the hub assembly and including a torque assembly lumen, and a guidewire co-axially disposed within the catheter lumen, hub assembly lumen, and torque assembly lumen. In a first configuration the torque assembly may be configured to simultaneously torque the elongate shaft and the guidewire and in a second configuration the torque assembly may be configured to torque the guidewire independent of the elongate shaft.

Abstract: A system includes a bus interface and circuitry. The bus interface is configured to communicate with an external device over a peripheral bus. The circuitry is configured to support a plurality of widgets that perform primitive operations used in implementing peripheral-bus devices, to receive a user-defined configuration, which specifies a user-defined peripheral-bus device as a configuration of one or more of the widgets, and to implement the user-defined peripheral-bus device toward the external device over the peripheral bus, in accordance with the user-defined configuration.

Abstract: An Artificial Intelligence (AI)-based data processing system processes current data to determine if the quality of the current data is adequate to be provided to data consumers and if the quality is adequate, the current data is further analyzed to determine if an impacted load including changes to dimension data of the current data or an incremental load including changes to fact data of the current data is to be provided to the data consumers. Depending on the amount of data to be provided to the data consumers, processing units (PUs) may be determined and assigned to carry out the data upload. Various machine learning (ML) models that are used to provide predictions from the current data are analyzed to determine the quality of predictions and if needed, can be automatically retrained by the data processing system.

Abstract: A voltage level-shifting circuit for an integrated circuit includes an input terminal receiving a voltage signal referenced to an input/output (I/O) voltage level. A transistor overvoltage protection circuit includes a first p-type metal oxide semiconductor (PMOS) transistor includes a source coupled to the second voltage supply, a gate receiving an enable signal, and a drain connected to a central node. A first n-type metal oxide semiconductor (NMOS) transistor includes a drain connected to the central node, a gate connected to the input terminal, and a source connected to an output terminal. A second NMOS transistor includes a drain connected to the input terminal, a gate connected to the central node, and a source connected to the output terminal.

Abstract: The system comprises a prediction module (1) equipped with artificial intelligence to predict neurological disorders in an individual patient and identify a level of neurological disorders; a central processing unit (2) to detect triggering events and circumstances due to which the neurological disorders trigger in an individual patient upon receiving real-time behavior information data generated by a playing ball (3) of an individual patient and distinguish between a normal behavior and a neurological disorders behavior; an alert module (4) to alert the individual patient upon determining neurological disorders behavior; and an entertainment platform (5) to entertain and engage the individual patient with a specific set of activities assigned according to detected triggering events and circumstances upon determining the neurological disorders behavior, wherein a specific set of activities includes listening to music, playing games, and talking to an AI chatbot.

Abstract: Computer-implemented systems and methods for training a decentralized model for making a personalized recommendation.

Abstract: Systems and methods for automated message delivery feedback that includes receiving a plurality of messaging requests to transmit a plurality of messages to a plurality of recipient devices, identifying subsets of related messaging requests in the plurality of messaging requests, receiving a plurality of delivery feedbacks for the plurality of messages, for each of the subsets of the related messaging requests, determining, based on the plurality of delivery feedbacks, whether to initiate at least one repeated transmission of a respective message to at least one recipient device, and upon determining to initiate the at least one repeated transmission, monitoring a delivery status of the respective message to the at least one recipient device.

Abstract: Systems and methods for entity recommendation can make use of rich data by allowing the items to be recommended and the recipients of the recommendation (e.g., users) to be modeled as “complex entities” composed of one or more static sub-entities and/or a dynamic component, and by utilizing information about multiple relationships between the sub-entities as reflected in bipartite graphs. Generating recommendations from such information may involve creating vector representations of the sub-entities based on the bipartite graphs (e.g., using graph-based convolutional networks), and combining these vector representations into representations of the items and users (or other recipients) to be fed into a classifier model.

Abstract: Systems and methods for processing inputs using attention neural networks with tree attention layers. Each tree attention layer includes one or more tree attention sub-layers that are each configured to: process query vectors using a decision tree model for the tree attention sub-layer to determine a respective tree path for each query vector; process key vectors using the decision tree model to determine a respective tree path for each key vector; and generate an attended input sequence comprising a respective attended input at each of the plurality of input positions, comprising: generating, for each particular input position, the respective attended input at the particular input position based on (i) the tree path for the query vector at the particular input position (ii) the respective tree paths for the key vectors at each of the plurality of input positions and (iii) the value vectors at a subset of the input positions.

Abstract: Methods and systems for aligning amplification gains in a plurality of interconnected devices are disclosed. The method includes receiving by each device limiter gain attenuations and brownout gain attenuations broadcasted by the plurality of devices and selecting the maximum brownout gain attenuation and the maximum limiter gain attenuation. The method includes determining a total attenuation as a sum of the maximum brownout attenuation gain and the maximum limiter attenuation gain. The method includes receiving a frame synchronization signal and adjusting the amplification gain by applying the total attenuation responsive to the frame synchronization signal.

Abstract: Systems and methods for automated message delivery feedback that includes receiving a set of messaging requests to transmit a message to at least one recipient device; making a set of messaging attempts, each of the set of messaging attempts including an attempt to deliver the message to the at least one recipient device; receiving delivery feedback and automatically associating the delivery feedback to one messaging attempt of the set of messaging attempts; and updating a delivery status of the at least one messaging attempt.

Abstract: A resource control system is described that is configured to control scheduling of executable jobs by compute instances of a service provider system. In one example, the resource control system outputs a deployment user interface to obtain job information. Upon receipt of the job information, the resource control system communicates with a service provider system to obtain logs from compute instances implemented by the service provider system for the respective executable jobs. The resource control system uses data obtained from the logs to estimate utility indicating status of respective executable jobs and an amount of time to complete the executable jobs by respective compute instances. The resource control system then employs a machine-learning module to generate an action to be performed by compute instances for respective executable jobs.

Abstract: The method receives a first request to establish a trusted relationship with a second client account of the SaaS platform. The trusted relationship enables sharing, with the second client account, of a client asset associated with the first client account. The method determines whether the first request satisfies one or more conditions related to the trusted relationship. The method stores an indication of the trusted relationship between the first client account and the second client account in a data store. The method receives a second request to perform a communication operation based on the client asset associated with the first client account. The method performs the communication operation on behalf of the second client account using the client asset associated with the first client account and based on the indication of the trusted relationship between the first client account and the second client account.

Abstract: An Artificial Intelligence (AI)-based data processing system processes current data to determine if the quality of the current data is adequate to be provided to data consumers and if the quality is adequate, the current data is further analyzed to determine if an impacted load including changes to dimension data of the current data or an incremental load including changes to fact data of the current data is to be provided to the data consumers. Depending on the amount of data to be provided to the data consumers, processing units (PUs) may be determined and assigned to carry out the data upload. Various machine learning (ML) models that are used to provide predictions from the current data are analyzed to determine the quality of predictions and if needed, can be automatically retrained by the data processing system.

Abstract: In an embodiment, a method includes matching terms of a received query to a database of provider capabilities. The method further includes determining, for each portion of the received query, a respective provider to execute the portion of the received query. The method further includes sending each portion of the received query to its respective provider. The method further includes combining results from each respective provider to a returned query result.

Abstract: Algorithm for tolerance analysis, allocation, and synthesis, also known as tolerance budgeting, is discussed. Also discussed is a metric to rank compensators for a system. It is based on the system Jacobian and the inner product of the output vector error as the tolerancing criterion. These tolerances are calculated by fitting an appropriate, axis aligned multidimensional Orthotope within an ellipsoid like region that is not necessarily axis aligned.

Abstract: An artificial intelligence based system and method for predicting and preventing illicit behavior is disclosed. The system and method may include obtaining search strings used by multiple users, as well as the clickstream data of such users. The search terms included in the search strings may be preprocessed and analyzed for inclusion of suspicious words, e.g., words related to illicit behavior, provided in a corpus of suspicious words. Information associated with the search strings containing suspicious words may be analyzed to identify users associated with the same search strings. The clickstream of the identified users may be analyzed to determine whether the users are likely to engage in illicit behavior. Preventive measures may be taken to prevent such users from engaging in such illicit behavior.