Abstract: Systems and methods for estimating battery degradation of a battery energy storage system (BESS) are disclosed. An iterative process is executed over a pre-defined time period divided into iterations. For each iteration, an average temperature of the BESS is determined by inputting a state of health (SOH) and charge rate into an average temperature look-up-table (LUT). The SOH for the next iteration is determined by inputting the determined average temperature into a set of cell degradation equations. The charge rate for the next iteration is derived from a usage profile which defines the charging and discharging cycles over the pre-defined time period and includes power and SOC over the pre-defined time period. The SOH of the BESS over the pre-defined time period may then be displayed on a user interface.

Abstract: An adjustable headphone system includes a headband configured to be worn on a user's head and one or more speaker modules that are adjustable between a proximate position adjacent to the user's ear and an offset position spaced apart from the ear. In the offset position, the speaker modules are configured to deliver audio while allowing ambient sound to reach the user's ear through an open acoustic path. In some embodiments, the headband includes a top portion with arms extending from opposite ends, each arm supporting a mechanical linkage with a hinged end and a free end to which a speaker module is mounted. The mechanical linkages may be rotatably coupled to the arms, and the speaker modules may be continuously or discretely adjustable between positions.

Abstract: Systems and methods for determining a total chargeable/dischargeable energy of a subsystem of a battery energy storage system (BESS) are disclosed. An iterative process is executed over a dynamic time period divided into iterations using a neural network model comprising an energy prediction sub-model and a state prediction sub-model. The energy prediction sub-model outputs a chargeable/dischargeable energy of the subsystem for the current iteration. The state prediction sub-model outputs a voltage of the subsystem for a next iteration, the charge rate of the subsystem for the next iteration, the maximum temperature of the subsystem for the next iteration, and a charge rate difference for the next iteration. A total chargeable/dischargeable energy of the BESS subsystem is determined by summing the dischargeable energies determined for each iteration.

Abstract: Systems and methods for estimating battery degradation of a battery energy storage system (BESS) are disclosed. An iterative process is executed over a pre-defined time period divided into iterations. For each iteration, an average temperature of the BESS is determined by inputting a state of health (SOH) and charge rate into an average temperature look-up-table (LUT). The SOH for the next iteration is determined by inputting the determined average temperature into a set of cell degradation equations. The charge rate for the next iteration is derived from a usage profile which defines the charging and discharging cycles over the pre-defined time period and includes power and SOC over the pre-defined time period. The SOH of the BESS over the pre-defined time period may then be displayed on a user interface.

Abstract: In one embodiment, a computer implemented method for merchandising a store is disclosed. The method may include, generating by a processing element a data object representation of the store from a digital model of the store, rendering by the processing element a structural plan of the store from the data object representation of the store, receiving by the processing element a merchandising placement specifying a placement of a first merchandising category at a first position within the structural plan, generating by the processing element a merchandising plane including the first merchandising category position at the first position, wherein the first position is related to a location in the store, and outputting to a display the merchandising plan.

Abstract: An Artificial Intelligence (AI) system trained by a plurality of training data. The AI system is trained by relationships between a time to final menstrual period and ratios between follicle-stimulating hormone levels and estradiol levels, race, cholesterol levels, and a presence of one or more contraceptives. The AI system is configured to accept data from only one sample from a user as input and generate a prediction of a time to final menstrual period for the user as output.

Abstract: An Artificial Intelligence (AI) system trained by a plurality of training data. The AI system is trained by relationships between a time to final menstrual period and ratios between follicle-stimulating hormone levels and estradiol levels, anti-mullerian hormone, race, cholesterol levels, and a presence of one or more contraceptives. The AI system is configured to accept data from only one sample from a user as input and generate a prediction of a time to final menstrual period for the user as output.

Abstract: Systems and methods for detecting intermittent connections in a battery energy storage system (BESS) subsystem are disclosed. For each battery rack in the BESS subsystem, current time series data is received. A current rolling average is determined for each data point of the time series data by averaging current values of timestamps over a specified time interval. A current delta is determined for each data point, where the current delta is a difference between the current rolling average associated with the battery rack under analysis and a mean of the current rolling averages associated with the other battery racks in the BESS subsystem. A distribution profile of the current deltas is analyzed to detect a current anomaly at the respective battery rack. In response to detecting the current anomaly at the battery rack under analysis, an alert indicative of a faulty connection is displayed on a user interface.

Abstract: A computer system comprising a processor and a memory storing instructions that, when executed by the processor, cause the computer system to perform a set of operations. The set of operations comprises collecting domain attribute data comprising one or more domain attribute features for a domain, collecting sampled domain profile data comprising one or more domain profile features for the domain and generating, using the domain attribute data and the sampled domain profile data, a domain reputation assignment utilizing a neural network.

Abstract: Systems and methods for optimizing charging and discharging of a battery energy storage system (BESS) are disclosed. A pre-defined time period mapped to electricity price forecast data is partitioned into charging windows and discharging windows. A bidding profile may be generated by identifying combinations of charging windows and discharging windows that maximize a revenue value over the pre-defined time period. A power profile for the BESS derived from the bidding profile is generated, and a battery analytics profile derived from the power profile is generated. The battery analytics profile is assessed for compliance with convergence criteria. If the battery analytics profile complies with the convergence criteria, the bidding profile is transmitted to a server of an electricity market operator for approval, otherwise, the bidding profile is adjusted until the resulting battery analytics profile complies with the convergence criteria.

Abstract: Systems and methods for determining a total chargeable/dischargeable energy of a subsystem of a battery energy storage system (BESS) are disclosed. An iterative process is executed over a dynamic time period divided into iterations using a neural network model comprising an energy prediction sub-model and a state prediction sub-model. The energy prediction sub-model outputs a chargeable/dischargeable energy of the subsystem for the current iteration. The state prediction sub-model outputs a voltage of the subsystem for a next iteration, the charge rate of the subsystem for the next iteration, the maximum temperature of the subsystem for the next iteration, and a charge rate difference for the next iteration. A total chargeable/dischargeable energy of the BESS subsystem is determined by summing the dischargeable energies determined for each iteration.

Abstract: Systems and methods for estimating battery degradation of a battery energy storage system (BESS) are disclosed. An iterative process is executed over a pre-defined time period divided into iterations. For each iteration, an average temperature of the BESS is determined by inputting a state of health (SOH) and charge rate into an average temperature look-up-table (LUT). The SOH for the next iteration is determined by inputting the determined average temperature into a set of cell degradation equations. The charge rate for the next iteration is derived from a usage profile which defines the charging and discharging cycles over the pre-defined time period and includes power and SOC over the pre-defined time period. The SOH of the BESS over the pre-defined time period may then be displayed on a user interface.

Abstract: A computer system comprising a processor and a memory storing instructions that, when executed by the processor, cause the computer system to perform a set of operations. The set of operations comprises collecting domain attribute data comprising one or more domain attribute features for a domain, collecting sampled domain profile data comprising one or more domain profile features for the domain and generating, using the domain attribute data and the sampled domain profile data, a domain reputation assignment utilizing a neural network.

Abstract: A battery system includes a plurality of batteries including a plurality of chargeable battery cells, and a bus to which the plurality of batteries are selectively connected in parallel. A battery management system monitors operating limits of the chargeable battery cells of the plurality of batteries, generates a signal indicating that an operating limit of a chargeable battery cell of a battery among the plurality of batteries is being reached for a foldback operation of the battery, and initiates the foldback operation. A controller is configured to generate a signal to disconnect the battery associated with the signal of the battery management system from the bus.

Abstract: A method of troubleshooting an application includes receiving, from an analytics engine, data representing a performance metric of the application and a tenant identifier associated with the application; sending, to the analytics service, a request to receive at least one user identifier associated with the tenant identifier; receiving, from the analytics service, at least one user identifier; selecting, from a database, a message based at least in part on the performance metric of the application; and sending the message to the application associated with the at least one user identifier.

Abstract: A communal computing device, such as an interactive digital whiteboard, can become unlocked if a user is near the device. The communal computing device may use a sensor such as a camera to capture images of a person and obtain an identifier from a personal device such as a smartphone. A cloud-based provider that is trusted by both the communal computing device and the personal device may associate both the image and the identifier of the personal device with the same user identity. Obtaining the user identity from multiple, different sources provides a secure technique for the communal computing device to recognize a user without the user directly interacting with the communal computing device. If the sensor no longer detects the user or the personal device is no longer detected, then the communal computing device may log off the user. The personal device may be used to confirm log off.

Abstract: Described embodiments provide systems, methods, and computer readable media for generating environment descriptors. A device having at least one process may identify a plurality of feature vectors. Each vector may describe a corresponding access to an application hosted on a server in one of a plurality of network environments and having a corresponding performance metric. The device may provide a performance model using the plurality of feature vectors and the corresponding performance metrics. The performance model may be used to determine expected performance metrics for at least a first network environment. A first environment descriptor of the expected performance metrics may be generated for at least the first network environment. The first environment descriptor of the expected performance metrics may be used to assess a measured performance metric or a second environment descriptor of a second network environment.

Abstract: Methods, systems, apparatuses, and computer-readable storage mediums described herein enable a dashboard panel application to make “widgets” available to a user on a computing device that provide application functionality without corresponding applications having to be installed on the computing device, and without the use of a conventional web browser. Configuration information is accessed that identifies a plurality of widgets selected for display in a dashboard panel of a dashboard panel application. Account credentials for the widgets are transmitted to corresponding server-hosted services at network addresses indicated in manifests of the widgets. Data associated with the widgets is received from the server-hosted services. A view of the dashboard panel is composed that includes a view of the widgets incorporating the received data. The dashboard panel view is caused to be rendered on the base graphical canvas.

Abstract: A dashboard panel application provides a content immersion experience. The dashboard panel application enables a user to scroll through headlines from multiple endpoints and delve deeper into a topic of interest while continuing to scroll the headlines from the same scrolling position. A first dashboard panel view including a first scrollable arrangement of content cards is caused to be rendered on a base graphical canvas. Each card is related to a respective content item. When a card is selected, the scroll state is stored, and the first dashboard panel view is dismissed. Additional content related to the selected card is displayed in a content immersion viewer pane. A second dashboard panel view comprising a second scrollable arrangement of the content cards is caused to be rendered with the content immersion viewer pane, and the scroll state is re-applied. The dashboard panel and content immersion viewer panes are independently scrollable.

Abstract: A communal computing device, such as an interactive digital whiteboard, can become unlocked if a user is near the device. The communal computing device may use a sensor such as a camera to capture images of a person and obtain an identifier from a personal device such as a smartphone. A cloud-based provider that is trusted by both the communal computing device and the personal device may associate both the image and the identifier of the personal device with the same user identity. Obtaining the user identity from multiple, different sources provides a secure technique for the communal computing device to recognize a user without the user directly interacting with the communal computing device. If the sensor no longer detects the user or the personal device is no longer detected, then the communal computing device may log off the user. The personal device may be used to confirm log off.