Abstract: A system and method for split rendering immersive media using proxy edge cloud computing architecture. The system and method may include dynamically determining a task-split or splitting a task for rendering a scene in an immersive media stream into two or more computational tasks based on one or more processing delays, wherein the task-splitting splits the scene into first part including one or more first tasks performed by an edge computing system and second part including one or more second tasks performed by a cloud computing system. The system and method may include transmitting the first parts of the scene, and transmitting the second parts of the scene.

Abstract: Horizontally-scalable systems and methods for scheduling and optimizing deliveries are described herein. At least one scheduler is configured to receive a request to schedule a delivery for an origination location. The request includes a desired time slot. The request is compared to a persistent delivery snapshot for the origination location to determine availability of the desired time slot. An interim delivery snapshot including the requested delivery is generated when the persistent delivery snapshot has an available time slot corresponding to the desired time slot. At least one optimizer is configured to receive the interim delivery snapshot and generate an updated persistent delivery snapshot by applying an optimization process to the interim delivery snapshot.

Abstract: A multiphase controller includes an integrator enable terminal, a pulse width modulator, an error integrator, an open drain driver, and an integrator enable circuit. The integrator enable terminal is adapted to be coupled to the integrator enable terminal of a different instance of the multiphase controller. The pulse width modulator is configured to modulate a power stage. The error integrator is configured to control the pulse width modulator. The open drain driver is coupled to the integrator enable circuit. The integrator enable circuit is coupled to the pulse width modulator, the error integrator, the open drain driver, and the integrator enable terminal. The integrator enable circuit is configured to activate the open drain driver responsive to generation of a power stage control pulse by the pulse width modulator, and activate the error integrator responsive to a logic low signal at the integrator enable terminal.

Abstract: A three dimensional glass ceramic article with a thickness between 0.1 mm and 2 mm, having a dimensional precision control of less than or equal to ±0.1 mm. A method for forming a three dimensional glass ceramic article including placing a nucleated glass article into a mold, and heating the nucleated glass article to a crystallization temperature, where the nucleated glass article is in the mold during the heating. Then, holding the nucleated glass article at the crystallization temperature for a duration sufficient to crystallize the nucleated glass article and form a three dimensional glass ceramic article, where the nucleated glass article is in the mold during the holding, and removing the three dimensional glass ceramic article from the mold.

Abstract: Methods and systems disclosed herein describe obfuscating plaintext cryptographic material stored in memory. A random location in an obfuscation buffer may be selected for each byte of the plaintext cryptographic material. The location of each byte of the plaintext cryptographic material may be stored in a position tracking buffer. To recover the scrambled plaintext cryptographic material, the location of each byte of the plaintext cryptographic material may be read from the position tracking buffer. Each byte of the plaintext cryptographic material may then be read from the obfuscation buffer and written to a temporary buffer. When each byte of the plaintext cryptographic material is recovered, the plaintext cryptographic material may be used to perform one or more cryptographic operations. The scrambling techniques described herein reduce the likelihood of a malicious user recovering plaintext cryptographic material while stored in memory.

Abstract: An example methodology implementing the disclosed techniques includes receiving an online meeting Uniform Resource Locator (URL) for an online meeting that is being scheduled. The method also includes determining whether the online meeting is a secure online meeting. The method also includes, responsive to a determination that the online meeting is a secure online meeting, generating a personalized online meeting URL for each meeting participant that is invited to the secure online meeting, the personalized online meeting URL being based on the online meeting URL. The method further includes encrypting the generated personalized online meeting URLs and sending to each meeting participant that is invited an invitation to the secure online meeting. The invitation sent to each invited meeting participant includes an encrypted personalized online meeting URL that is generated for that invited meeting participant.

Abstract: A method is performed by a network node connected to one or more additional network nodes via a local area network (LAN). The network node and the one or more additional network nodes form a cloud. The method includes setting a first timer to a first value, the first timer being associated with determining whether one of the one or more additional network nodes is an active controller in the cloud. The method includes starting the first timer. The method includes determining, before the first timer expires, whether a first message that indicates the one of the one or more additional network nodes is the active controller is received. Based on determining the first message is received before the first timer expires, the method includes synchronizing with the one of the one or more additional network nodes that is the active controller, and restarting the first timer.

Abstract: Disclosed herein are examples of systems and methods for formatting electronic messages using machine learning. An electronic message can be obtained, and a processed message can be generated based at least in part on the electronic message. At least one attribute for the processed message can be determined. A formatting specification can be generated based at least in part on the at least one attribute. A reformatted message can be generated based at least in part on the formatting specification.

Abstract: Described is a technology that facilitates directory level snapshots at any level of a filesystem's namespace. A directory inode mapping file associates a first directory's virtual inode number(s) with real inode number(s). A snapshot of the first directory creates a second directory with a second directory inode mapping file copied from the first directory inode mapping file, thereby sharing the real inode data structure(s) of the first directory. In the event that one of the directories is to be modified, the directory real inode is split to provide a new directory real inode file for the to-be-modified directory, with the modification after the split.

Abstract: Systems and methods for supporting regulatory requirements for the distribution of controlled and non-controlled items such as, for example, non-controlled prescriptions (Rx), medical devices, and controlled substances in countries such as the United States and Canada, are provided. The systems and methods incorporate a license verification module that is configured to perform license validation for a particular order placed for a controlled and/or non-controlled item. In certain embodiments, the license verification module compares order data to historically sorted data and if one or more discrepancies exist, validation is unsuccessful. The license verification module may further query a third party database for updated license information upon validation failure.

Abstract: A method includes selecting first features to be machined within a first tolerance range, and second features, which are located at least a predetermined distance apart, to be machined within a second tolerance range of a specified dimension for the selected features. The method includes machining, using a cutting attachment of a tool, the first features within the first tolerance range, and when a parameter associated with the tool causing variation in dimension of the first selected features reaches a predetermined threshold, machining, using the cutting attachment, the second selected features within the second tolerance range. In a second method, a mean value of dimensions of the first and second features is less than or equal to a predetermined mean deviation from the specified dimension, and a standard deviation of the dimensions of the first and second features is less than or equal to a predetermined standard deviation.

Abstract: A method performed by a network node connected to one or more additional network nodes, the network node and the one or more additional network nodes forming a cloud. The method including setting a first timer to a first value, the first timer associated with determining whether another network node from the one or more additional network nodes is an active controller in the cloud. The method further includes determining, before the first timer expires, whether a first message that indicates that another network node from the one or more additional network nodes is the active controller is received. The method further includes based on determining the first message is received before the first timer expires, restarting the first timer. The method further includes, based on determining the first message is not received before the first timer expires, assigning one or more tasks to at least one network node.

Abstract: A method for teleconference includes receiving a first media stream that carries a first audio, and a second media stream that carries a second audio, and receiving a first audio weight for weighting the first audio and a second audio weight for weighting the second audio. The first audio weight and the second audio weight are different from each other and determined based on at least one of (i) content of the first audio and content of the second audio or (ii) received customization parameters. The method further includes generating a mixed audio by combining a weighted first audio based on the first audio weight and a weighted second audio based on the second audio weight.

Abstract: A method of biasing speech recognition includes receiving audio data encoding an utterance and obtaining a set of one or more biasing phrases corresponding to a context of the utterance. Each biasing phrase in the set of one or more biasing phrases includes one or more words. The method also includes processing, using a speech recognition model, acoustic features derived from the audio data and grapheme and phoneme data derived from the set of one or more biasing phrases to generate an output of the speech recognition model. The method also includes determining a transcription for the utterance based on the output of the speech recognition model.

Abstract: Stable lyophilized immunogenic compositions include inter alia live attenuated recombinant flaviviruses, more preferably live attenuated recombinant dengue viruses, at least one carbohydrate, at least one amino acid and is particularly amenable to rapid freeze-drying treatments wherein, the composition preserves desired characteristics of a virus, including virus viability, immunogenicity and stability. The immunogenic composition is devoid of preservatives, polymers and surfactants. The methods for manufacturing the stable lyophilized immunogenic compositions are also provided.

Abstract: Provided is a system and method that can identify whether an item is a dangerous good. The system can determine whether a product belongs in any of a number of different classes of dangerous goods from among a plurality of different regulations based on a machine learning algorithm which performs a text-based classification. In one example, the method may include receiving an identification of an object, retrieving a plurality of descriptive attributes of the object from a data store and converting the plurality of descriptive attributes into an input string, predicting whether the object is a dangerous object via execution of a text-based machine learning algorithm that receives the input string as an input, and outputting information about the prediction of the object for display via a user interface.

Abstract: A method for authorization of multiple transactions using a single authentication process is described. The method includes determining that a user is an authorized user based on user credentials associated with the user; authorizing a transaction device identified by the authorized user for future electronic transactions with one or more restrictions; and providing previously stored payment card information associated with a user account of the authorized user for electronic transactions initiated at the authorized transaction device in accordance with the one or more restrictions.

Abstract: The present invention relates to a process for the production of a roasted plant material with oil. The oil used for roasting the plant material comprises the fatty acids C16:0 in the range of 1 to 25 wt% (based on weight of total fat) and C18:1 in the range of 60 to 90 wt% (based on weight of total fat) and C18:2 in the range of 0.1 to 20 wt% (based on weight of total fat).

Abstract: Embodiments relate to an aligner breakage solution that tests damage to an aligner using machine learning. A method includes of training a machine learning model to predict damage to an orthodontic aligner includes gathering a training dataset comprising digital designs for a plurality of orthodontic aligners, wherein each digital design is associated with a respective orthodontic aligner of the plurality of orthodontic aligners, and wherein each digital design comprises metadata indicating whether the associated respective orthodontic aligner was damaged during manufacturing of the associated respective orthodontic aligner. The method further includes training the machine learning model using the training dataset, wherein the machine learning model is trained to process data from a digital design for an orthodontic aligner and to output a probability that the orthodontic aligner associated with the digital design will be damaged during manufacturing of the orthodontic aligner.