Abstract: A method for managing security in a cloud computing environment. The method includes obtaining metadata related to the deployment of an application, where the deployment is associated with one or more cloud resources. The method assigns first labels to the cloud resources based on the metadata and second labels based on user input. These labels may include environment and application identifiers. A security ruleset is then generated based on the assigned labels and applied to the resources associated with the application deployment. The method continuously monitors metadata to detect changes in the application and updates the security ruleset accordingly to ensure ongoing protection and control over network traffic involving the application resources.

Abstract: The dental care device comprises a drive mechanism and a customized mouthpiece. The drive mechanism comprises a first motor connection point, a second motor connection point, and one or more motors. The customized mouthpiece is configured to couple with the drive mechanism, and comprises: a first region including a first mouthpiece connection point configured to engage with the first motor connection point; a second region including a second mouthpiece connection point configured to engage with the second motor connection point; and a third region connection the first region and the second region, such that the first region can be moved independently of the second region.

Abstract: A method and a system for migrating a computing environment from a first platform to a second platform are disclosed. The method includes identifying a first set of components associated with the first platform and a second set of components associated with the second platform. The method further includes comparing the first set of components with the second set of components. Further, the method includes mapping the first set of components with the second set of components based on the comparison. The method further includes introducing the first set of components in the second platform based on the mapping. Further, the method includes updating at least one interface associated with the second platform for interaction with at least one entity. Thereafter, the method includes enriching, using a trained model, the second set of components associated with the second platform.

Abstract: Changing environmental characteristics of an enclosure are controlled to promote thermal comfort, health, wellness, and/or performance for occupant(s) of the enclosure using sensor data, three-dimensional modeling, physical properties of the enclosure, and machine learning (e.g., Artificial Intelligence).

Abstract: This disclosure relates to systems and methods for multi-utterance generation of data. Embodiments of the present disclosure utilizes a smart framework that is capable of generating contextually relevant utterances with immutability regulation and punctuation-memory. More Specifically, the present disclosure generates multiple syntactically and semantically correct utterances for text input data in such a way that a provision to selectively maintain or regulate phrases or words intact is provided and punctuation consistency is maintained.

Abstract: An apparatus, having a server and processor, is configured to receive a first set of security rules applicable to a set of users or a set of files for a first period of time. The first set of security rules are executable in an order of priority. The processor receives an interim security policy that is different from the first set of security rules. The interim security policy is applicable to a subset of the set of users for a second period of time that is less than the first period, or a subset of the set of files for a second period of time that is less than the first period. The processor determines, in the first set of security rules, an insertion point among the order of priority. The processor executes, at the insertion point and in the first set of security rules, the interim security policy.

Abstract: Data from measurements is used in conjunction with a learning module to identify and predict tintable window malfunctions. The measurements can be based at least in part on data accumulated during regular operation of a tintable window.

Abstract: Techniques are provided for body position correction. In one embodiment, the techniques involve receiving an image of a body, determining a body position based on the image, wherein the body position includes a movement, a pose, a posture, or a stance of the body, mapping markers to positions of the body, determining a body position angle, generating a correction angle of the body based on a comparison between the body position angle and a standard body position angle, and displaying a correction message.

Abstract: Techniques for providing centralized identity redistribution for a security service are disclosed. In some embodiments, a system/process/computer program product for providing centralized identity redistribution for a security service includes receiving user context information (e.g., an IP-user mapping, a user-tag mapping, an IP-tag mapping, an IP-port-user mapping, an IP-device ID mapping, 5G user context information, and/or other user context information/data) at a security platform from a cloud security service; and applying a security policy at the security platform using the user context information.

Abstract: An integrated circuit (IC) device includes one or more functional blocks spanning a lithographic seam between adjacent lithographic fields. A functional block includes multiple instances of a pattern, each instance corresponding to a different placement option for the functional block. The IC device may include multiple such functional blocks spanning lithographic fields. The lithographic seam (and the patterns otherwise located) may include lithographic assist features, such as registration marks and metrology structures. The multiple lithographic fields may be or include high numerical aperture extreme ultraviolet lithographic fields. The lithographic seam may interface with wafer finishing collaterals (such as guard rings).

Abstract: In one embodiment, an integrated circuit structure includes a first transistor device comprising a first gate stack and a second transistor device comprising a second gate stack. The second transistor device is spaced a first distance laterally from the first transistor device. The structure further includes a dielectric region between the first gate stack and the second gate stack. The dielectric region is spaced a second distance laterally from the first transistor device, where the first distance is substantially twice the second distance.

Abstract: A current state is identified at a current time based on incidents occurring in a lookback window. Whether an incident that meets predefined criteria is likely to occur in a prediction window is predicted using a machine-learning model based on the current state. The machine-learning model is trained based on training data obtained from historical data. Each training datum of the training data includes a training lookback window and a training prediction window. Each training lookback window is used to identify incidents occurring in the each training lookback window. Each training prediction window is used to identify whether at least one incident that meets the predefined criteria occurred in the each training prediction window. In response to predicting that the incident that meets the predefined criteria is likely to occur, a notification is transmitted indicating that the incident that meets the predefined criteria is predicted to occur.

Abstract: Incidents in a lookback window from a current time are identified based on selection criteria. A current state is identified based on the incidents. A subset of objects of interest that are likely to occur in a prediction window is identified using a machine-learning (ML) model and based on the current state. The ML model is a k-nearest neighbors model that is trained based on training data obtained from historical data. Each training datum of the training data includes a training lookback window and a training prediction window. Each training lookback window is used to identify incidents occurring in the each training lookback window. Each training prediction window is used to identify which of the objects of interest occurred in the each training prediction window. A notification is transmitted or displayed indicating the subset of the objects of interest.

Abstract: System and method for fine granularity control of data access and usage for across multi-tenant systems. A user makes a request to access a particular set of data from a particular remote data source for a specific purpose. The system authorizes the user to validate whether the user is qualified to make the request. The data source is checked to see if the particular data has been granted access for that particular purpose. A cloud neutral token is created and converted into a cloud specific token upon reaching the remote data source. The cloud specific token is used to create a temporary IAM role and IAM policy with a predetermined time to live. After the time to live expires, the IAM role and IAM policy are deleted.

Abstract: An IC device may include functional regions as well as replica cells and filler cells that can reduce local layout effect in the IC device. A functional region includes functional cells, e.g., logic cell or memory cells. A white space may be between a first functional region and a second functional region. A first portion of the white space may be filled with replica cells, each of which is a replica of a cell in the first functional region. A second portion of the white space may be filled with filler cells that are not functional. The first function region is closer to the replica cells than to the filler cells. A third portion of the white space may be filled with replica cells, each of which is a replica of a cell in the second functional region. The second portion is between the first portion and the third portion.

Abstract: System and method for fine granularity control of data access and usage for across multi-tenant systems. A user makes a request to access a particular set of data from a particular remote data source for a specific purpose. The system authorizes the user to validate whether the user is qualified to make the request. The data source is checked to see if the particular data has been granted access for that particular purpose. A cloud neutral token is created and converted into a cloud specific token upon reaching the remote data source. The cloud specific token is used to create a temporary IAM role and IAM policy with a predetermined time to live. After the time to live expires, the IAM role and IAM policy are deleted.

Abstract: System and method for fine granularity control of data access and usage for across multi-tenant systems. A user makes a request to access a particular set of data from a particular remote data source for a specific purpose. The system authorizes the user to validate whether the user is qualified to make the request. The data source is checked to see if the particular data has been granted access for that particular purpose. A cloud neutral token is created and converted into a cloud specific token upon reaching the remote data source. The cloud specific token is used to create a temporary IAM role and IAM policy with a predetermined time to live. After the time to live expires, the IAM role and IAM policy are deleted.

Abstract: System and method for fine granularity control of data access and usage for across multi-tenant systems. A user makes a request to access a particular set of data from a particular remote data source for a specific purpose. The system authorizes the user to validate whether the user is qualified to make the request. The data source is checked to see if the particular data has been granted access for that particular purpose. A cloud neutral token is created and converted into a cloud specific token upon reaching the remote data source. The cloud specific token is used to create a temporary IAM role and IAM policy with a predetermined time to live. After the time to live expires, the IAM role and IAM policy are deleted.

Abstract: A method and system include receiving current data values for a group of vehicles, each of the current data values being generated by vehicles in the group of vehicles, and retrieving data external to the group of vehicles. They further include processing the data using two or more machine learning algorithms to identify a set of selected data values based on current operation and processing the set of selected data values, using a first and second machine learning algorithm, to generate predicted efficiency values for each vehicle. They further include determining if a predicted efficiency value of a first vehicle in the group of vehicles is less than a predicted efficiency for a second vehicle in the group of vehicles, comparing operational characteristics of the first and second vehicle based on the determination, and providing a message in order to improve efficiency for the first vehicle based on the comparison.

Abstract: Methods, computing systems, and technology for optimizing a landing page of a website are presented. The system can receive, from a user device, a first web address associated with a first webpage of the website. The system can process, using the machine-learned assessment model, the first webpage to generate a first landing page score. The system can determine, based on the first landing page score and using a machine-learned optimization model, an actionable suggestion associated with the landing page. The system can cause, on a display of the user device, a presentation of the actionable suggestion.