Abstract: An example operation may include one or more of generating a plurality of successive data points of an iterative simulation based on predefined checkpoints, each data point identifying an evolving state of the iterative simulation with respect to a previous data point among the successive data points, transmitting a blockchain request for validating state data within a first data point among the plurality of successive data points to a first subset of endorsing nodes of a blockchain network, and transmitting a blockchain request for validating state data within a second data point among the plurality of successive data points to a second subset of endorsing nodes which are mutually exclusive from the first subset of endorsing nodes of the blockchain network for parallel endorsement of the first and second data points.

Abstract: An example operation may include one or more of obtaining data of a simulation, identifying checkpoints within the simulation data, generating a plurality of sequential data structures based on the identified checkpoints, where each data structure identifies an evolving state of the simulation with respect to a previous data structure among the sequential data structures, and transmitting the generated sequential data structures to nodes of a blockchain network for inclusion in one or more data blocks within a hash-linked chain of data blocks.

Abstract: An example operation may include one or more of obtaining data of a simulation, identifying checkpoints within the simulation data, generating a plurality of sequential data structures based on the identified checkpoints, where each data structure identifies an evolving state of the simulation with respect to a previous data structure among the sequential data structures, and transmitting the generated sequential data structures to nodes of a blockchain network for inclusion in one or more data blocks within a hash-linked chain of data blocks.

Abstract: It is not trivial to implement speech and natural language processing in offline embedded systems. Voice control of devices in various settings and applications can benefit from an embedded speech and natural language processing solution. One feature that helps to correct automatic speech recognition outputs is grammar projection. Another feature addresses situations where there is imperfect information or incomplete information by providing an application programming interface to enable structured queries and responses between an interpreter and an application.

Abstract: One embodiment is a system for estimating an internal temperature of a battery including a first circuit for receiving a system input signal comprising a measurement of at least one observable quantity associated with the battery and outputting an average battery temperature signal based on the system input signal; and an estimator for receiving the system input signal and the average battery temperature signal and estimating an internal temperature of the battery based on the received signals, wherein the estimator comprises a lumped thermal model of the battery comprising a plurality of parameters.

Abstract: An example operation may include one or more of generating a data frame storing content of a simulation, compressing the simulation content within the data frame based on previous simulation content stored in another data frame to generate a compressed data frame, and transmitting the compressed data frame via a blockchain request to one or more endorsing peer nodes of a blockchain network for inclusion of the compressed data frame within a hash-linked chain of blocks of the blockchain network.

Abstract: An example operation may include one or more of generating a data frame storing content of a simulation, compressing the simulation content within the data frame based on previous simulation content stored in another data frame to generate a compressed data frame, and transmitting the compressed data frame via a blockchain request to one or more endorsing peer nodes of a blockchain network for inclusion of the compressed data frame within a hash-linked chain of blocks of the blockchain network.

Abstract: An example operation may include one or more of obtaining data of a simulation, identifying checkpoints within the simulation data, generating a plurality of sequential data structures based on the identified checkpoints, where each data structure identifies an evolving state of the simulation with respect to a previous data structure among the sequential data structures, and transmitting the generated sequential data structures to nodes of a blockchain network for inclusion in one or more data blocks within a hash-linked chain of data blocks.

Abstract: An example operation may include one or more of obtaining data of a simulation, identifying checkpoints within the simulation data, generating a plurality of sequential data structures based on the identified checkpoints, where each data structure identifies an evolving state of the simulation with respect to a previous data structure among the sequential data structures, and transmitting the generated sequential data structures to nodes of a blockchain network for inclusion in one or more data blocks within a hash-linked chain of data blocks.

Abstract: Examples for distributed and secure storage of a data block amongst a network of nodes are presented. An example embodiment may involve logically partitioning the network of nodes into non-overlapping zones, each zone containing a subset of the nodes and generating a private key for use within a particular zone. The embodiment may further involve encrypting the data block with the private key, partitioning the data block as encrypted into sub-blocks, and distributing the sub-blocks amongst a subset of the nodes that is within the particular zone. The embodiment may also involve using a secret sharing process to divide the private key into a number of shares equivalent to a number of nodes in the particular subset of the nodes and distributing the shares of the private key amongst the particular subset of the nodes, such that each node therein receives exactly one of the shares of the private key.

Abstract: A Laser Imaging Detection and Ranging (LIDAR) system comprises a memory configured to store LIDAR measurement data obtained by the LIDAR system representative of a three-dimensional (3D) space in a field of view of the LIDAR system and signal processing circuitry. The signal processing circuitry is and configured to convert the LIDAR measurement data to a voxel characteristic of voxels of the 3D space, process and adjust a voxel characteristic of a first voxel of the 3D space using a voxel characteristic of other voxels within a specified distance of the first voxel in the 3D space, continue to process and adjust the voxel characteristics of all voxels in the 3D space, and generate an indication of presence of an object in the field of view according to the adjusted voxel characteristics.

Abstract: An example operation may include one or more of obtaining data of a simulation, identifying checkpoints within the simulation data, generating a plurality of sequential data structures based on the identified checkpoints, where each data structure identifies an evolving state of the simulation with respect to a previous data structure among the sequential data structures, and transmitting the generated sequential data structures to nodes of a blockchain network for inclusion in one or more data blocks within a hash-linked chain of data blocks.

Abstract: An example operation may include one or more of generating a data frame storing content of a simulation, compressing the simulation content within the data frame based on previous simulation content stored in another data frame to generate a compressed data frame, and transmitting the compressed data frame via a blockchain request to one or more endorsing peer nodes of a blockchain network for inclusion of the compressed data frame within a hash-linked chain of blocks of the blockchain network.

Abstract: An example operation may include one or more of generating a plurality of successive data points of an iterative simulation based on predefined checkpoints, each data point identifying an evolving state of the iterative simulation with respect to a previous data point among the successive data points, transmitting a blockchain request for validating state data within a first data point among the plurality of successive data points to a first subset of endorsing nodes of a blockchain network, and transmitting a blockchain request for validating state data within a second data point among the plurality of successive data points to a second subset of endorsing nodes which are mutually exclusive from the first subset of endorsing nodes of the blockchain network for parallel endorsement of the first and second data points.