Honeywell International Inc.

Infrrd Inc.

Oracle International Corporation

Deepak Kumar

Prashant Deshpande

Ritu Rai

Pranita Madke

Sridhar Vanka

Mauruthi Geetha Mohan

Surya Raichor

Madhu Manjunath

Muralidhar Manavalan

Mukesh Shah

Frederick Anthonisamy Bosco

Apurv Awasthi

Akshay Mall

Mayank Bajpai

Bharat Shivram

Raj Miglani

Prashantha Sv

Jianglong He

Prakash V S

Anubhab Patra

Prakash Bist

Shiv Rai

An identity service in a cloud environment is communicatively coupled to a proxy key vault in the cloud environment and to an external key manager (EKM) located outside of the cloud environment. The identity service receives a token request for a communication credential from the proxy key vault and verifies the request based on a client credential associated with the proxy key vault. The identity service generates the client credential and signs the communication credential with a private key associated with the EKM. The identify service transmits the signed communication credential to the proxy key vault. The communication credential can be used to substantiate cryptographic operation requests to the EKM.

System and method for two way trust between an external key management system and a cloud computing infrastructure

System for optimizing training dataset comprising sample documents. The system comprises one or more processors configured to create graph embedding vector for each of the sample documents of the training dataset and cluster the graph embedding vectors of the sample documents of the training dataset into clusters based on the similarity between the graph embedding vectors. Further, the processor is configured to select a first set of training data, using an optimization model, wherein the first set of training data comprises a finite number of graph embedding vectors of the sample documents from the clustered training dataset. Finally, the first set of training data is fed as for a machine learning model.

System for optimizing training dataset

An example system includes a turbine comprising an input port and mechanically coupled to a motor-generator and a compressor and control circuitry configured to determine whether a pressure of a fluid at the input port of the turbine is less than or equal to than a threshold pressure. In response to determining that the pressure of the fluid at the input port of the turbine is less than or equal to the threshold pressure, the control circuitry is configured to cause the motor-generator to operate in motor mode. The motor-generator is configured to be mechanically coupled to the compressor, and the motor-generator is configured to provide mechanical energy to drive the compressor when operating in motor mode.

Environmental control system

A device includes a processor or integrated circuit package and at least one MEMS device coupled to the processor or integrated circuit package. The at least one MEMS device includes a first arm, a second arm, at least one permanent magnet, a fan structure, and a coil. The second arm is coupled to, and is spaced apart from, the first arm. The at least one permanent magnet is coupled to the first arm. The fan structure is coupled to, and extends in cantilever manner from, the second arm. The coil is disposed on or within the fan. Thus, when the coil is electrically energized, a Lorentz force is generated that causes the fan structure to vibrate relative to the at least one permanent magnet and relative to the processor, to thereby cool the processor or integrated circuit package.

Processors and integrated circuits including a microelectromechanical systems (MEMS) device for cooling

A system for template invariant information extraction. The system comprises of processor, a first neural network model and a second neural network model. The processor is configured to recognize and extract entities and location of the entities in the input document using the first neural network model. The processor is further configured to classify whether the input document belongs to at least a template of the documents of the first training dataset using the second neural network model. The second neural network model comprises a linear classifier configured to generate a plurality of confidence scores for the input document corresponding to a unique template of the documents of the first training dataset. A threshold value to classify the input document belonging to template of the documents of the first training dataset is determined, Classification is done by comparing the confidence score with the threshold value.

System for template invariant information extraction

A system to calculate a reconfigured confidence score is configured to receive a text, a plurality of labels, and a plurality of confidence scores from a plurality of models and assign a weightage to the inputs received from the plurality of models. The system is configured to select a first text with a first label and retrieve a second text, a third text, and a second label. The system is further configured to generate a first, second and third output confidence score for the first text, second text and third text, and corresponding labels. The system compares the plurality of output confidence scores and generates an output which comprises of the first text, the first label, and a final confidence score, wherein the final confidence score is one among the first, second and third output confidence scores.

System to calculate a reconfigured confidence score

A microelectromechanical systems (MEMS) device and a light assembly that includes the MEMS device. The MEMS device includes a first arm, a second arm, at least one permanent magnet, a fan structure, and a coil. The first arm has a first arm first end and a first arm second end. The second arm is coupled to, and is spaced apart from, the first arm and has a second arm first end and a second arm second end. The at least one permanent magnet is coupled to the first arm second end. The fan structure is coupled to, and extends in cantilever manner from, the second arm second end and includes a connection end and a free end. The coil is disposed on or within the fan structure. When the coil is electrically energized, a Lorentz force is generated that causes the fan structure to vibrate relative to the permanent magnet.

Microelectromechanical systems (MEMS) device and an aircraft exterior light assembly including the same

The present invention discloses a system for linking first type of entities and second type of entities in a page. The system is configured to generate a feature vector for each of the first type of entities and each of the second type of entities. Further, the system is configured to receive into a neural network, a pair of the feature vectors, wherein one of the pair of the feature vector corresponds to a feature vector of a first type of entity and another feature vector corresponds to a feature vector of a second type of entity. The entities corresponding to the pair of feature vectors are neighboring each other. The neural network is configured to generate an output, indicating the likelihood of the pair of entities being linked.

System for identifying and linking entity relationships in documents

Systems and methods for temperature measurement. In an example embodiment, two or more arrays of multi-spot temperature elements can be implemented, wherein at least one array among the two or more arrays constitutes a primary temperature measurement array and at least one other array among the two or more arrays constitutes a redundant temperature measurement array. The redundant temperature measurement array includes redundant spot temperature elements equivalent to spot temperature elements associated with the primary temperature measurement array. A transmitter assembly can also be provided, which communicates electronically with the aforementioned two or more arrays, and which processes and controls such arrays of the multi-spot temperature elements. The secondary (redundant) elements can be configured from the same material as that of the primary spot element(s) or can be composed of a different material depending on the sensor type (e.g., thermcouple, thermistor, etc.).

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Bengaluru, India

Deepak Kumar