Abstract: Predicting energy production for energy generating assets, including: receiving current and forecasted meteorological data associated with a location of an energy generating asset; and predicting an energy production value produced by the energy generating asset at a predetermined time based on the current and forecasted meteorological data using a trained model for the energy generating asset, the trained model being trained using a machine learning algorithm that utilizes historical meteorological data associated with the location of the energy generating asset and historical production capability data associated with a historical production capability of the energy generating asset.

Abstract: Distributed firewalls in a network are disclosed. Example firewall controllers disclosed herein are to instruct a first network node of a software-defined network to implement a first firewall instance of a distributed firewall, the first network node to implement the first firewall instance with a first virtual machine. Disclosed example firewall controllers are also to configure a second network node of the software-defined network to route network traffic through the first firewall instance and, after at least some of the network traffic is dropped by the first firewall instance, instruct the second network node to implement a second firewall instance of the distributed firewall, the second network node to implement the second firewall instance with a second virtual machine.

Abstract: The present disclosure discloses a data science driven system and associated methodology framework for mining relevant knowledge from input/output traces of a closed-loop control system for glycemic control to aid in actionable feedback for Type 1 diabetes management. The framework takes Continuous Glucose Monitor (CGM) records and insulin pump records from a closed loop control (CLC) system and interprets the CGM records and insulin pump data to provide medically useful information, wherein the closed-loop control system is operable for operation in an “auto mode” (AP) and a “manual mode” (SAP).

Abstract: A system examines components of gestures of a gesture-based language for evaluating proper execution of the gesture, and also examines components of new gestures for evaluating lexical similarity with existing gestures of similar meaning or theme.

Abstract: A cache may store critical cache lines and non-critical cache lines, and may attempt to retain critical cache lines in the cache by, for example, favoring the critical cache lines in replacement data updates, retaining the critical cache lines with a certain probability when victim cache blocks are being selected, etc. Criticality values may be retained at various levels of the cache hierarchy. Additionally, accelerated eviction may be employed if the threads previously accessing the critical cache blocks are viewed as dead.

Abstract: An apparatus includes a plurality of processor circuits, a cache memory circuit, and a trace control circuit. The trace control circuit may be configured, in response to activation of a mode to record information indicative of program execution of at least one processor circuit of the plurality of processor circuits, to monitor memory requests transmitted between ones of the plurality of processor circuits and the cache memory circuit, and then to select a particular memory request of monitored memory requests using an arbitration algorithm. The trace control circuit may be further configured to allocate space in a trace buffer to the particular memory request, and to store, in the trace buffer, information associated with the particular memory request.

Abstract: A cache may store critical cache lines and non-critical cache lines, and may attempt to retain critical cache lines in the cache by, for example, favoring the critical cache lines in replacement data updates, retaining the critical cache lines with a certain probability when victim cache blocks are being selected, etc. Criticality values may be retained at various levels of the cache hierarchy. Additionally, accelerated eviction may be employed if the threads previously accessing the critical cache blocks are viewed as dead.

Abstract: A workflow construction system for constructing automation workflows that automate user specific processes. The workflow construction system may include a template library including workflow templates and pre-configured attributes. The workflow template can accelerate the design and construction of custom automation workflows. An orchestration layer included in the workflow construction system will also improve the performance of systems that execute the automation workflows by dynamically scaling the processing capacity, memory, and storage of servers and other systems hosting the model file instances of the automation workflows to ensure the available resources meet the demands of users completing processes using the automation workflows.

Abstract: Safety certification of cyber-physical system (CPS) such as autonomous cars or medical control systems are complicated especially due to the lack of transparency between the manufacturer and certifying authority. The manufacturer has significant restrictions in sharing knowledge with the certification authority. Further, given time constraints, it may not be feasible for the certification authority to examine internal details of the CPS. A system models the safety certification of CPS as an agile iterative game, where a manufacturer agent acting on behalf of the manufacturer and a certifier agent acting on behalf of a third-party certification entity aims to find an optimal subset of operating data to share for accurate safety certification. The certification agent, armed with CPS model mining methods and safety assessment analysis tools, aims to accurately assess safety of the CPS with the information shared.

Abstract: Complexities arising from interaction between multiple inter-connected components in an autonomous cyber physical system can potentially result in differences in intended and observed operations of a CPS. To perform fault analysis of a CPS it is imperative to explain this discrepancy in terms of the components of CPS control code. A system estimates a “mined” hybrid system representation of a CPS based on observed input/output traces and extracts a state machine representation of the CPS control code. The system compares the “mined” hybrid system representation with the extracted state machine representation simplification of the CPS code to identify discrepancies between expected and observed operation of the CPS. The system explains discrepancies in terms of call conditions as binary or unary operations on input and output variables and status of function call arguments.

Abstract: Various embodiments of systems and methods for mobile crowd sensing applications are disclosed herein.

Abstract: Methods and systems for utilizing co-simulation of a physical model and a self-adaptive predictive controller using hybrid automata are described. For example, there is disclosed a self-adaptive predictive control system to generate an initial patient model with initial patient model settings (k1, k2, . . . , kn) and execute a program that takes as input, the initial patient model settings as configuration parameters that specify at least a plurality of initial states. Such a system further receives new patient inputs and generates hybrid automata as a variation of the initial states by applying the new patient inputs to the initial patient model. The system further derives reachable states from the hybrid automata and outputs all reachable states computed. The system further detects changes and responsively generates a new patient predictive model with new parameter settings (k?1, k?2, . . . , k?n), iteratively repeating until a termination criterion is satisfied. Other related embodiments are disclosed.

Abstract: Systems and methods are provided for controlling predictive medical monitoring. A non-linear-predictive-guide model estimates a patient parameter that is used as a guide in a deep neural network for improving accuracy of estimation by the deep neural network. The guide model generates a guiding first estimated patient parameter based on the guide model and patient input data. The deep neural network generates a second estimated patient parameter based on the deep neural network, the patient input data, and the guiding first estimated patient parameter. The deep neural network includes an input layer that receives the guiding first estimated patient parameter, and hidden layers including respective artificial neurons configured to perform a linear or nonlinear transformation on output of at least one artificial neuron from an adjacent layer in the deep neural network. An output layer receives at least one output from a hidden layer.

Abstract: A workflow construction system for constructing automation workflows that automate user specific processes. The workflow construction system may include a template library including workflow templates and pre-configured attributes. The workflow template can accelerate the design and construction of custom automation workflows. An orchestration layer included in the workflow construction system will also improve the performance of systems that execute the automation workflows by dynamically scaling the processing capacity, memory, and storage of servers and other systems hosting the model file instances of the automation workflows to ensure the available resources meet the demands of users completing processes using the automation workflows.

Abstract: Various embodiments of systems and methods for mobile crowd sensing applications are disclosed herein.

Abstract: A workflow construction system for constructing automation workflows that automate user specific processes. The workflow construction system may include a template library including workflow templates and pre-configured attributes. The workflow template can accelerate the design and construction of custom automation workflows. An orchestration layer included in the workflow construction system will also improve the performance of systems that execute the automation workflows by dynamically scaling the processing capacity, memory, and storage of servers and other systems hosting the model file instances of the automation workflows to ensure the available resources meet the demands of users completing processes using the automation workflows.

Abstract: Various embodiments of systems and methods for a learning environment for accessible virtual computer science education are disclosed.

Abstract: Systems and methods for generating a custom document template are disclosed. An example method may be performed by one or more processors of a system and include retrieving a user document including a user data entry in a user data field, identifying a set of system data fields within a plurality of system documents potentially relevant to the user document, determining, for each of the set of system data fields, a weighted value indicative of a likelihood that the system data field is relevant to the user data field, identifying a most relevant system data field of the set of system data fields, the most relevant system data field having a highest weighted value of the determined weighted values, and generating a custom document template including a dynamic data region for the user data entry, the dynamic data region mapped to the most relevant system data field.

Abstract: Various embodiments of a system and associated method for evaluating handwashing protocol compliance are disclosed herein. The system considers temporal combinations of segments of a test handwashing routine to recognize components of a compliant handwashing routine within the test handwashing routine. The system determines whether the components of the handwashing routine have been adequately performed and provides actionable feedback to a user to improve adherence to handwashing routine guidelines.

Abstract: Various embodiments of a system and associated method for language-driven gesture understanding are disclosed herein.