Abstract: A system and method for acquiring an image. The method includes dropping an object into free fall, detecting the dropping of the object, triggering a plurality cameras to simultaneously image the object in parallel, while the object drops into a bottom half of an imaging sphere at a center of a field of view of each of the plurality of cameras, upon detecting the dropping of the object, analyzing images of the imaged object in parallel, based on a trained machine learning model, and displaying a three dimensional image of a surface of the object based on the analysis of the images of the imaged object.

Abstract: A system, method and apparatus to automatically perform endotracheal intubation in a patient comprising, inserting a blade inside the upper airway of the patient to retract an anatomical structure; inserting a bending portion and a tube arranged on the bending portion inside the airway of the patient; collecting airway data using at least one imaging sensor arranged on the bending portion; communicating collected airway data to a processing circuitry; predicting an intended path for insertion of the tube and generating control signals using the processing circuitry, wherein the intended path is predicted based on at least one anatomical structure recognized by the processing circuitry using the collected airway data; displaying an intended path via a user interface to display at least one intended path to an operator and also allow the operator to select an intended path; and communicating the control signals generated by the processing circuitry to at least one actuation unit to actuate the three-dimensional

Abstract: A retraining monitoring system maintains the sustainability of a production machine learning (ML) model system that includes a production ML model retraining platform. The retraining monitoring system collects contextual data from the production ML model system and determines if one or more of a currently-selected architectural options has to be changed for sustainability. An architectural option of the production ML model retraining platform, such as, a processing location is selected from a cloud retraining platform or an on-premises retraining platform by a selection process based on a multi-armed bandit problem. An evaluation of the retraining architecture is dealt with as a reinforcement learning problem to implement one of a periodic retraining architecture or a reactive retraining architecture.

Abstract: A system and method for acquiring an image. The method includes dropping an object into free fall, detecting the dropping of the object, triggering a plurality cameras to simultaneously image the object in parallel, while the object drops into a bottom half of an imaging sphere at a center of a field of view of each of the plurality of cameras, upon detecting the dropping of the object, analyzing images of the imaged object in parallel, based on a trained machine learning model, and displaying a three dimensional image of a surface of the object based on the analysis of the images of the imaged object.

Abstract: A first device may provide, via a global digital twin of the first device, a communication mode assignment, of a communication mode, to a local digital twin of a second device. The communication mode assignment is to cause the local digital twin to communicate with the global digital twin via the communication mode. The first device may generate, via the global digital twin, a task assignment, and may provide, via the global digital, the task assignment to the local digital twin. The first device may update, via the global digital twin, a model based on the task assignment, and may receive, via the global digital twin and from the local digital twin, a model update associated with the local digital twin. The first device may update, via the global digital twin, the model based on the model update.

Abstract: A method and system for cloud distributed hybrid data storage and normalization are disclosed. The method may include obtaining a data set comprising data entities. A data entity may comprise data fields each containing a data element. The method may further include determining policy constraint meta-data for each of the data elements based on the storage policy constraint. The policy constraint meta-data may include a first meta-tag indicating the storage policy constraint for the data element. The method may further include determining whether a server satisfies the storage policy constraint based on the first meta-tag for the data element. When the server satisfies the storage policy constraint, the method may further include transmitting the data element to the server to store the data element on the server. When the server fails to satisfy the storage policy constraint, the method may further include, storing the data element on the client.

Abstract: Aspects of the present disclosure provide methods, devices, and computer-readable storage media that support detection, effect monitoring, and recovery from failure modes in cloud computing application using a failure mode effect analysis (FMEA) engine. Historical metadata related to operation of a hierarchy of devices may be used as training data to train the FMEA engine to identify failure modes experienced by the hierarchy of devices. After training the FMEA engine, metadata from the hierarchy of devices may be input to the FMEA engine to identify a failure mode that may have occurred, and the FMEA engine may select a recovery process to recommend for addressing or mitigating the identified failure mode. In some implementations, the FMEA engine may output an indication of the recommended recovery process and/or initiate performance of one or more operations at the hierarchy of devices to recover from the failure event.

Abstract: A method and system for cloud distributed hybrid data storage and normalization are disclosed. The method may include obtaining a data set comprising data entities. A data entity may comprise data fields each containing a data element. The method may further include determining policy constraint meta-data for each of the data elements based on the storage policy constraint. The policy constraint meta-data may include a first meta-tag indicating the storage policy constraint for the data element. The method may further include determining whether a server satisfies the storage policy constraint based on the first meta-tag for the data element. When the server satisfies the storage policy constraint, the method may further include transmitting the data element to the server to store the data element on the server. When the server fails to satisfy the storage policy constraint, the method may further include, storing the data element on the client.

Abstract: A method and system for cloud distributed hybrid data storage and normalization are disclosed. The method may include obtaining a data set comprising data entities. A data entity may comprise data fields each containing a data element. The method may further include determining policy constraint meta-data for each of the data elements based on the storage policy constraint. The policy constraint meta-data may include a first meta-tag indicating the storage policy constraint for the data element. The method may further include determining whether a server satisfies the storage policy constraint based on the first meta-tag for the data element. When the server satisfies the storage policy constraint, the method may further include transmitting the data element to the server to store the data element on the server. When the server fails to satisfy the storage policy constraint, the method may further include, storing the data element on the client.

Abstract: In one embodiment, a manufacturing process is optimized by enabling a user to specify a product to be manufactured, enabling the user to specify a manufacturing system for manufacturing the product, enabling the user to select parameters for the product and the manufacturing system, and automatically calculating manufacturing metrics for the manufacturing process based upon the user-specified models and user selections.

Abstract: In one embodiment, a manufacturing system includes multiple manipulation modules each including means for mechanically and electrically connecting the module to another component in the system and an end effector including means for mechanically and electrically connecting the end effector to another component in the system, wherein the modules and end effector can be mechanically and electrically connected in multiple ways to alter the configuration of the system and the manufacturing tasks that the system can perform.

Abstract: In one embodiment, a manufacturing process is optimized by enabling a user to specify a product to be manufactured, enabling the user to specify a manufacturing system for manufacturing the product, enabling the user to select parameters for the product and the manufacturing system, and automatically calculating manufacturing metrics for the manufacturing process based upon the user-specified models and user selections.

Abstract: In one embodiment, a manufacturing system includes multiple manipulation modules each including means for mechanically and electrically connecting the module to another component in the system and an end effector including means for mechanically and electrically connecting the end effector to another component in the system, wherein the modules and end effector can be mechanically and electrically connected in multiple ways to alter the configuration of the system and the manufacturing tasks that the system can perform.

Abstract: The present invention relates to an improved process of analytical and quantitative isolation of withaferin-A from Withania somnifera (Sanskrit: Ashwagandha, English: winter cherry) and other plants and products therefrom, said method comprising steps of selecting most appropriate extraction medium composition, with extraction solvent system consisting of a defined admixture of water and alcohol in a range of proportion of alcohol within a narrow range of (methanol, ethanol etc.

Abstract: The invention provides a non-chrome rinse and method for treating a phosphate conversion-coated ferrous metal substrate. The rinse comprising zirconium ions, vanadium ions, fluoride ions, and phosphate ions in a ratio and a concentration effective for providing the phosphate conversion-coated ferrous metal substrate with improved corrosion resistance.

Abstract: An aqueous, acidic composition for application to aluminum and aluminum alloy surfaces comprising a source of zirconium ions, a source of fluoride ions, a source of phosphate ions, a phosphate acid ester, a polyethylene glycol ester of a fatty acid, and nitric acid, and a method for treating aluminum and aluminum alloy surfaces with such a composition.

Abstract: An aqueous composition for treating metal surfaces, particularly formed aluminum and aluminum alloy surfaces, comprising a surface tension reducing agent selected from the group consisting of sulfosuccinate salts and derivatives and mixtures thereof, a surfactant selected from the group consisting of propoxylated and ethoxylated linear alcohols, and an acid such as phosphoric acid, as well as preferably a bactericide and a defoamant, and a method for treating metal surfaces, particularly beverage containers, such as of aluminum and aluminum alloy with such a composition.

Abstract: An aqueous, acidic composition for application to aluminum and aluminum alloy surfaces comprising a source of zirconium ions, a source of fluoride ions, a source of phosphate ions, a phosphate acid ester, a polyethylene glycol ester of a fatty acid, and nitric acid, and a method for treating aluminum and aluminum alloy surfaces with such a composition.

Abstract: An aqeuous acidic composition provides improved coating for aluminum. The composition comprises from about 10 to about 150 ppm zirconium, from about 20 to about 250 ppm fluoride, from about 30 to about 125 ppm tannin, from about 15 to about 100 ppm phosphate and from about 5 to about 50 ppm zinc, said coating solution having a tannin to phosphate ratio in the range of at least about 1:1 to about 2:1 and a pH in the range of about 2.3 to about 2.95.

Abstract: A low pH solution and a method for conversion coating aluminum and aluminum alloy surfaces, as well as the coated surfaces themselves, utilizing zirconium, fluoride and nickel and, optionally, fluorophosphate.