Abstract: An appliance includes an external communication port, such as an RJ45 port, and a wireless communication module in wireless communication with a remote server through an external network. A controller is configured to receive, using the wireless communication module, a secure unlock command from a remote server, the secure unlock command being generated when a remote service device transmits appliance identification data to the remote server, and unlock the external communication port to permit the remote service device to access operating software through the external communication port.

Abstract: Embodiments described herein are directed to an annotation system having a remote processor, and a client processor in data communication with the remote processor. The client processor is adapted to send a first request for an electronic file to the remote processor, receive the electronic file from the remote processor, define at least one new annotation about the electronic file, and define at least one anchor associated with the at least one annotation. The at least one of the remote processor and the client processor is adapted to store the at least one anchor and the at least one annotation in an annotation file that is separate from the electronic file.

Abstract: The technology described herein trains a reinforcement-learning model in a simulated environment. A simulated environment contrasts with a live environment. A live environment is a computing environment with which the reinforcement-learning model will interact once it is deployed. In order to be effective, the simulated environment may provide inputs to the reinforcement-learning model in the same format as the reinforcement-learning model receives from the live environment. In aspects, the training in the simulated environment may act as pre-training for training in the live environment. Once pre-trained, the reinforcement-learning model may be deployed in a live environment and continue to learn how to perform the same task in different ways, learn how to perform additional tasks, and/or improve performance of a task learned in pre-training. In aspects, the reinforcement-learning model may be used to discover unhealthy conditions in software by performing the tasks it has learned.

Abstract: The technology described herein provides an automated software-testing platform that functions in an undefined action space. The technology described herein starts with an undefined action space but begins to learn about the action space through random exploration. Both the action taken during testing and the resulting state may be communicated to a centralized testing service. The technology described herein also mines the action telemetry data and state telemetry data to identify action patterns that produce a sought after result. Once a plurality of action patterns is identified and, at least, a partial model of the action space is built, the testing on the test machines may be split into random test mode, replay test mode, and a pioneering test mode.

Abstract: The technology described herein provides a cloud reinforcement-learning architecture that allows a single reinforcement-learning model to interact with multiple live software environments. The live software environments and the single reinforcement-learning model run in a distributed computing environment (e.g., cloud environment). The single reinforcement-learning model may run on a first computing device(s) with a graphical processing unit (GPU) to aid in training the single reinforcement-learning model. At a high level, the single reinforcement-learning model may receive state telemetry data from the multiple live environments. The single reinforcement-learning model selects an available action for each set of state telemetry data received and communicates the selection to appropriate the test agent. The test agent then facilitates completion of the action within the software instance being tested in the live environment. A reward is then determined for the action.

Abstract: The technology described herein provides an automated software-testing platform that uses reinforcement learning to discover how to perform tasks used in testing. The technology described herein is able to perform quality testing even when prescribed paths to completing tasks are not provided. The reinforcement-learning agent is not directly supervised to take actions in any given situation, but rather learns which sequences of actions generate the most rewards through the observed states and rewards from the environment. In the software-testing environment, the state can be user interface features and actions are interactions with user interface elements. The testing system may recognize when a sought after state is achieved by comparing a new state to a reward criteria.

Abstract: A solid state thin film battery including a plurality of solid state cells and a termination region is disclosed. Each cell is connected to the termination region by a current collector which includes a deformation element configured to deform under a lower load than the rest of the current collector. The properties, for example the geometry and/or materials of the portion of the current collector that forms the deformation element, may differ with respect to the properties of the rest of the current collector. Methods of manufacturing and operating such a battery are also disclosed.

Abstract: Various aspects described herein relate to a location-based and population-based health metric processes. In one example, a computer-implemented method for generating one or more predicted health metrics for a location includes receiving a request to assess the one or more health metrics associated with the location, and identifying at least one current or future built, social, or natural environment parameter associated with the location. The method may further include calculating one or more predicted health metrics associated with the location based upon at least one of the current or future built, social, or natural environment parameters associated with the location, monetizing the healthcare costs of the predicted health metrics and displaying the one or more predicted health metrics and costs.

Abstract: An electric vehicle AC charging system comprising a charging station connected to a source of AC power and including a first processor, the charging station being electrically connectable to an electric vehicle; and a charging station management system including a second processor. The first processor is configured to operate under a first communication protocol to communicate with said electric vehicle to obtain a vehicle ID and an initial state of charge of a vehicle connected to the plug; operate under a second communication protocol to communicate with said electric vehicle to advertise available current to said electric vehicle; measure vehicle power consumption data during charging of the electric vehicle; and operate under a third communication protocol to transmit the vehicle ID and initial state of charge data to the charging station management system and to transmit the vehicle power consumption data to the charging station management system.

Abstract: A social electronic learning system, including a plurality of computing devices for communicating with a plurality of users in an educational community, and at least one server in communication with each of the plurality of computing devices, each server in communication with at least one data storage device configured to host a plurality of electronic portfolios, each electronic portfolio associated with one or more users of the plurality of users in the educational community, wherein each server is configured such that one or more users may associate one or more digital items with each electronic portfolio, and the plurality of users may take actions on the digital items in each electronic portfolio depending on authorization criteria.

Abstract: A working machine includes a body, a ground-engaging propulsion structure supporting the body, a drive arrangement configured to provide motive power to the ground engaging propulsion structure, a braking system actuatable to apply a braking force to the ground engaging propulsion structure, a control system, and a sensor assembly configured to determine an output of the drive arrangement and to provide an output to the control system. The control system is configured to apply a first braking force to the ground engaging propulsion structure that is based on the determined output of the drive arrangement.

Abstract: Various aspects described herein relate to a location-based and population-based health metric processes. In one example, a computer-implemented method for generating one or more predicted health metrics for a location includes receiving a request to assess the one or more health metrics associated with the location, and identifying at least one current or future built, social, or natural environment parameter associated with the location. The method may further include calculating one or more predicted health metrics associated with the location based upon at least one of the current or future built, social, or natural environment parameters associated with the location, monetizing the healthcare costs of the predicted health metrics and displaying the one or more predicted health metrics and costs.

Abstract: A social electronic learning system, including a plurality of computing devices for communicating with a plurality of users in an educational community, and at least one server in communication with each of the plurality of computing devices, each server in communication with at least one data storage device configured to host a plurality of electronic portfolios, each electronic portfolio associated with one or more users of the plurality of users in the educational community, wherein each server is configured such that one or more users may associate one or more digital items with each electronic portfolio, and the plurality of users may take actions on the digital items in each electronic portfolio depending on authorization criteria.

Abstract: A computer-aided educational system and method to further a student's understanding of a subject matter through analyzing data captured in an electronic learning system so as to determine correlation data corresponding to variables or trends which are determined to enhance, optimize, and/or improve one's learning abilities or understanding of educational content. The system and method generates reports based on the correlation data, develops statistical models that highlight learning and behavioral trends, and/or provides recommendations for adapting the learning system based on the correlation data and statistical models.

Abstract: Embodiments described herein are directed to an annotation system having a remote processor, and a client processor in data communication with the remote processor. The client processor is adapted to send a first request for an electronic file to the remote processor, receive the electronic file from the remote processor, define at least one new annotation about the electronic file, and define at least one anchor associated with the at least one annotation. The at least one of the remote processor and the client processor is adapted to store the at least one anchor and the at least one annotation in an annotation file that is separate from the electronic file.

Abstract: Embodiments described herein are directed to an annotation system having a remote processor, and a client processor in data communication with the remote processor. The client processor is adapted to send a first request for an electronic file to the remote processor, receive the electronic file from the remote processor, define at least one new annotation about the electronic file, and define at least one anchor associated with the at least one annotation. The at least one of the remote processor and the client processor is adapted to store the at least one anchor and the at least one annotation in an annotation file that is separate from the electronic file.

Abstract: A computer-aided educational system and method to further a student's understanding of a subject matter through analyzing data captured in an electronic learning system so as to determine correlation data corresponding to variables or trends which are determined to enhance, optimize, and/or improve one's learning abilities or understanding of educational content. The system and method generates reports based on the correlation data, develops statistical models that highlight learning and behavioral trends, and/or provides recommendations for adapting the learning system based on the correlation data and statistical models.

Abstract: The present disclosure generally relates to magnetic liquid particles, and methods for using the magnetic liquid particles. More specifically, the present disclosure relates to magnetic liquid particles having antimicrobial properties. The particles can comprise a liquid metal core comprising a liquid gallium or alloy thereof, and a plurality of magnetic iron particles; and an inorganic passivation layer encapsulating the liquid metal core. The particles can be used for disrupting a biofilm. The particles can also be used for the treatment of biofilm related diseases.

Abstract: Various aspects described herein relate to a location-based and population-based health metric processes. In one example, a computer-implemented method for generating one or more predicted health metrics for a location includes receiving a request to assess the one or more health metrics associated with the location, and identifying at least one current or future built, social, or natural environment parameter associated with the location. The method may further include calculating one or more predicted health metrics associated with the location based upon at least one of the current or future built, social, or natural environment parameters associated with the location, monetizing the healthcare costs of the predicted health metrics and displaying the one or more predicted health metrics and costs.

Abstract: A computer-aided educational system and method to further a student's understanding of a subject matter through analyzing data captured in an electronic learning system so as to determine correlation data corresponding to variables or trends which are determined to enhance, optimize, and/or improve one's learning abilities or understanding of educational content. The system and method generates reports based on the correlation data, develops statistical models that highlight learning and behavioral trends, and/or provides recommendations for adapting the learning system based on the correlation data and statistical models.