Abstract: Various aspects of methods, systems, and use cases include techniques for training or using a model to control a robot. A method may include identifying a set of action primitives applicable to a set of robots, receiving information corresponding to a task (e.g., a collaborative task), and determining at least one action primitive based on the received information. The method may include training a model to control operations of at least one robot of the set of robots using the received information and the at least one action primitive.

Abstract: A device including a processor configured to detect an environment of an automated machine, wherein the environment comprises one or more further automated machines; determine an action taken by the one or more further automated machines; determine an action expected of the one or more further automated machines; compares the taken action with the expected action; determine an accuracy score associated with the one or more further automated machines based on the comparison.

Abstract: A controller for an automated machine may include including: one or more processors configured to: determine that a group affiliation of the automated machine switched from a first group of automated machines to a second group of automated machines, the first group of automated machines being assigned to one or more first tasks, the second group of automated machines being assigned to one or more second tasks; generate a message for one or more network devices of the second group of automated machines in accordance with a communication protocol, the message including information about a task performing model of the automated machine, the task performing model being based on a result of performing at least one task of the one or more first tasks by the automated machine.

Abstract: An apparatus, method, and computer-readable medium for a local attestation service of a network within a trust cluster. The apparatus comprises memory, machine-readable instructions, and processor circuitry configured to execute the machine-readable instructions to communicate with a selected node outside the trust cluster, attest the selected node, and, when attestation of the selected node is successful, register the selected node within the trust cluster.

Abstract: According to various aspects, a controller for an automated machine may include: one or more processors configured to: obtain a message from a further automated machine in accordance with a communication protocol, the message including a first result of a first sensing process that the further automated machine performs; and determine an assessment of the automated machine based on the first result and based on a second result of a second sensing process that the automated machine performs.

Abstract: Methods and systems that allow a user to see the people or groups who have access to files that are maintained by a plurality of cloud content sharing services. In particular, the user may see what specific party has access to each particular file or directory, regardless of multiple cloud content sharing services involved. Moreover, a user interface and exposed application program interface allows the user to manipulate the permissions, e.g., granting access, to another person or group, to a file or directory. The user interface may also allow the user to terminate access to the file or directory for a person or group. The user's action to change a permission may be effected independently of the particular cloud content sharing service.

Abstract: Various systems and methods for implementing a software defined industrial system are described herein. For example, an orchestrated system of distributed nodes may run an application, including modules implemented on the distributed nodes. In response to a node failing, a module may be redeployed to a replacement node. In an example, self-descriptive control applications and software modules are provided in the context of orchestratable distributed systems. The self-descriptive control applications may be executed by an orchestrator or like control device and use a module manifest to generate a control system application. For example, an edge control node of the industrial system may include a system on a chip including a microcontroller (MCU) to convert IO data. The system on a chip includes a central processing unit (CPU) in an initial inactive state, which may be changed to an activated state in response an activation signal.

Abstract: Embodiments herein relate to recognition of an appliance state based on sensor data and determination of a response based at least in part on the appliance state. In various embodiments, an apparatus to recognize an appliance state may include a sensor data module to identify sensor data in one or more signals relating to data from one or more sensors associated with an appliance, an appliance state recognition module to determine an appliance state of the appliance based at least in part on the sensor data, a response module to determine a response based at least in part on the appliance state, and a transmission module to send the response to at least one of an appliance controller for the appliance or a presentation device. Other embodiments may be described and/or claimed.

Abstract: In one embodiment, a method of training an autoencoder neural network includes determining autoencoder design parameters for the autoencoder neural network, including an input image size for an input image, a compression ratio for compression of the input image into a latent vector, and a latent vector size for the latent vector. The input image size is determined based on a resolution of training images and a size of target features to be detected. The compression ratio is determined based on entropy of the training images. The latent vector size is determined based on the compression ratio. The method further includes training the autoencoder neural network based on the autoencoder design parameters and the training dataset, and then saving the trained autoencoder neural network on a storage device.

Abstract: Various examples relate to apparatuses, devices, methods and computer programs for wrapping a monolithic application. In one aspect, such an apparatus is to observe a behavior of the monolithic application, and to provide a wrapper for wrapping the monolithic application, the wrapper comprising an interface that exposes one or more capabilities of the monolithic application to a microservice managing platform, with the interface being based on the observed behavior.

Abstract: A first computing system includes a data store with a sensitive dataset. The first computing system uses a feature extraction tool to perform a statistical analysis of the dataset to generate feature description data to describe a set of features within the dataset. A second computing system is coupled to the first computing system and does not have access to the dataset. The second computing system uses a data synthesizer to receive the feature description data and generate a synthetic dataset that models the dataset and includes the set of features. The second computing system trains a machine learning model with the synthetic data set and provides the trained machine learning model to the first computing system for use with data from the data store as an input.

Abstract: An apparatus including a memory and a processor configured to: identify an item located within the environment based on sensor data, wherein the sensor data represents one or more sensor detections of the environment; determine a metric representative of a likelihood of the item becoming lost the within the environment based on information about the item; and select, based on the metric, at least one monitoring method to monitor the item within the environment from a plurality of monitoring methods.

Abstract: Systems, apparatus, articles of manufacture, and methods are disclosed to identify causes of defects in industrial environments. An example apparatus includes interface circuitry to access data associated with an object in an environment and programmable circuitry to utilize machine-readable instructions. For example, the programmable circuitry is to identify a cause of a defect of the object based on a timeline of the object in the environment, the timeline based on the data.

Abstract: There is disclosed a system, including apparatus, methods and computer programs, for running native software applications (apps) and HTML5 web-based apps on a computing device, particularly a mobile computing device, in a multitasking mode of operation. In one embodiment, touch screen displays having one or more browsers are adapted to run one or more HTML5 apps, and receive input from hand gestures. One or more software modules execute on the operating system and are responsive to a dragging gesture applied to an HTML5 app displayed in a full screen mode, to subdivide the screen display and display the HTML5 app in one of the subdivided areas and display icons used to launch a second HTML5 app in a different one of the subdivided areas. The second HTML5 app is run concurrently with the first HTML5 app in order to provide multi-tasking between the first and second apps.

Abstract: Various systems and methods for implementing a software defined industrial system are described herein. For example, an orchestrated system of distributed nodes may run an application, including modules implemented on the distributed nodes. In response to a node failing, a module may be redeployed to a replacement node. In an example, self-descriptive control applications and software modules are provided in the context of orchestratable distributed systems. The self-descriptive control applications may be executed by an orchestrator or like control device and use a module manifest to generate a control system application. For example, an edge control node of the industrial system may include a system on a chip including a microcontroller (MCU) to convert IO data. The system on a chip includes a central processing unit (CPU) in an initial inactive state, which may be changed to an activated state in response an activation signal.

Abstract: Examples relate to a concept for software application container hardware resource allocation, and in particular to sidecar apparatuses, sidecar devices, methods for a software application container sidecars, a resource management controller apparatus, a resource management controller device, and corresponding computer programs and computer systems. A sidecar apparatus comprises interface circuitry, machine-readable instructions and processing circuitry to execute the machine-readable instructions to obtain information on hardware resources desired by a software application container from the software application container, and to provide a request for changing the hardware resources allocated to the software application container to another entity capable of influencing an allocation of hardware resources to the software application container.

Abstract: Examples relate to a computer system, a telemetry hub apparatus, a telemetry hub device, a telemetry hub method, a microservice apparatus, a microservice device, a microservice method and to corresponding computer programs. The telemetry apparatus is configured to obtain telemetry information from a plurality of microservices, and to provide access to the telemetry information for the plurality of microservices according to an access scheme.

Abstract: Various systems and methods for a collaborative phone reputation system are described herein. A system for implementing a collaborative phone reputation system includes a compute device comprising: a call handling module to detect, at the compute device, an incoming call for a user of the compute device; a scoring module to determine a local probabilistic score that the incoming call is desirable for the user; and an execution module to perform an action at the compute device based on the local probabilistic score.

Abstract: Various systems and methods may be used to implement a software defined industrial system. For example, an orchestrated system of distributed nodes may run an application, including modules implemented on the distributed nodes. The orchestrated system may include an orchestration server, a first node executing a first module, and a second node executing a second module. In response to the second node failing, the second module may be redeployed to a replacement node (e.g., the first node or a different node). The replacement mode may be determined by the first node or another node, for example based on connections to or from the second node.

Abstract: A technique allows a smart meter to receive a mask. The smart meter may receive the mask from a utility company or an escrow service. The smart meter may apply the mask to original metered data on a continuous schedule, on a periodic schedule, or on a determined schedule, or on a randomized schedule to conceal the original metered data. The smart meter may apply different masks at different times. The smart meter transmits the concealed metered data as augmented metered data remotely to an electric utility via a communication network.