Abstract: The present disclosure relates to systems, methods, and non-transitory computer-readable media for utilizing a parameterized notebook to adaptively generate visualizations regarding machine-learning models. In particular, the disclosed systems can generate a parameterized notebook based on a user-defined visualization recipe and provide parameter values that correspond to the machine-learning model to the parameterized notebook. Upon execution of the user-defined visualization recipe via the parameterized notebook, the disclosed systems can extract visualization data corresponding to the machine-learning model from the parameterized notebook. In addition, the disclosed systems can generate visualizations based on the visualization data and provide the generated visualizations for display in a graphical user interface.

Abstract: A system for executing software, wherein a computing device stores instructions for a code execution module such that, when the instructions are executed, the computing device will: receive, for execution by the code execution module, software; create one or more immutable software nodes described in the software; determine that the software comprise an instruction to begin a simulated change at runtime of the one or more immutable software nodes; store the simulated change in a simulated change apparatus; using the simulated change apparatus, perform one or more operations of the software as if the one or more immutable software nodes had been changed in memory, during a period of time where each of the one or more immutable software nodes is guaranteed to retain logical immutability; and output results of the one or more operations.

Abstract: An abnormality determination device acquires observation data observed during an operation of an industrial machine, extracts partial time-series data, including a portion representative of a feature of an operating state at a specified timing, from the observation data, calculates a statistical amount from the extracted partial time-series data, and performs processing for machine learning related to determination of operation abnormality of the industrial machine, based on the calculated statistical amount.

Abstract: Device security across multiple operating system modalities, including: allocating, by a hypervisor, to a first virtual machine comprising a first operating system, based on the first modality, a first one or more access privileges to one or more resources; allocating, by the hypervisor, to a second virtual machine comprising a second operating system, based on the second modality, a second one or more access privileges to the one or more resources; and modifying, by the hypervisor, the second one or more access privileges in response to a change in an execution state of the first virtual machine.

Abstract: Various embodiments provide a data analysis apparatus, system, and method. The data analysis apparatus may collect data of a network node in a mobile access network, and then perform data analysis and adjust a configuration parameter of the network node, to implement targeted data analysis and parameter adjustment for the network node, so that a speed of data analysis and configuration parameter adjustment can be improved. In addition, modules of the data analysis apparatus may run in parallel, so that the speed of data analysis and configuration parameter adjustment can be further improved.

Abstract: A method of motor control device emulation includes receiving, via a network-enabled motor control device, a communication request corresponding to an emulated motor control device. The method further includes modifying the communication request to match an expected communication request. Additionally, the method includes providing a modified communication request to an associated hardware module within the network-enabled motor control device. Further, the expected communication request is based on the network-enabled motor control device.

Abstract: A computer-implemented method, computer system, and computer program product for a container deployment simulation. The method may include performing a container deployment simulation. The method may include detecting a container deployment simulation error. In response to detecting the container deployment simulation error, the method may include providing one or more recommendations to a user. In response to receiving an acceptance of the recommendation from the user, the method may include implementing the recommendation. In response to receiving a rejection of the recommendation from the user, the method may include receiving a user recommendation. The method may include implementing the user recommendation and performing the container deployment simulation. The one or more recommendations may have a weight value. The weight value of the one or more recommendations may be increased when the user accepts the one or more recommendations or reduced when the user rejects the one or more recommendations.

Abstract: Closed loop performance controllers of asymmetric multiprocessor systems may be configured and operated to improve performance and power efficiency of such systems by adjusting control effort parameters that determine the dynamic voltage and frequency state of the processors and coprocessors of the system in response to the workload. One example of such an arrangement includes applying hysteresis to the control effort parameter and/or seeding the control effort parameter so that the processor or coprocessor receives a returning workload in a higher performance state. Another example of such an arrangement includes deadline driven control, in which the control effort parameter for one or more processing agents may be increased in response to deadlines not being met for a workload and/or decreased in response to deadlines being met too far in advance. The performance increase/decrease may be determined by comparison of various performance metrics for each of the processing agents.

Abstract: A method for updating an application is provided. In the method, a first interface image generated during a period that a first instance of the application is running is obtained. The first instance of the application is running on an application trial platform. The application trial platform is communicatively couplable to a server of the application. A plurality of attributes associated with a control contained in the first interface image are extracted. Based on the plurality of attributes, it is determined whether the first interface image indicates that an update of the application is released by the server. In response to determining that the first interface image indicates that the update of the application is released by the server, the first instance of the application is updated on the application trial platform.

Abstract: Certain aspects of the present disclosure provide techniques for establishing a web session between a computing device and a web-based integrated development environment to create and/or update files (e.g., content files and/or resource files). In the web session, content file(s) can be evaluated in real-time with one or more resource files. Further, in the web session, a set of validation rules of a resource file can be updated by the computing device. To stablish the web session, a first communication connection is established between the computing device and the web-based integrated development environment. With the first communication established, a second communication connection is established for real-time, bi-directional communication between the computing device and a language server instance of the web-based integrated development environment.

Abstract: A method includes identifying machine process parameters for an additive manufacturing process to produce a part, providing a real-world sensor to sense a characteristic associated with a real-world version of the additive manufacturing process, receiving sensor readings from the real-world sensor while the machine is performing the real-world version of the additive manufacturing process, generating, with a computer-based processor, physics-based features associated with the additive manufacturing process, and training a machine-learning software model based at least in part on the machine process parameters, the sensor readings, and the physics-based features to predict a behavior of the real-world sensor.

Abstract: Controllers that control a building's state functions can be controlled by a master controller that the controllers choose themselves. The master controller communicates with the controllers and sensors to determine when a building state should change. When the building state should change, the master controller or another controller determines the device or devices that need to modify state values of the building, and send messages to the devices so that they can change building state. If the master controller has a fault, the working controllers can choose another master controller. When a sensor indicates that a building state needs to be changed the master controller determines which device should change state, then tells the controller that is attached to the device.

Abstract: In an information processing apparatus (100), obtaining units such as a first obtaining unit (200) and a second obtaining unit (230) obtain general-purpose OS information in a test operation phase in which a real-time application and a plurality of general-purpose applications are executed. The general-purpose OS information is information on use of hardware by each of the plurality of general-purpose applications executed in the test operation phase. A management unit (220) verifies whether or not a condition to place a restriction on the use of the hardware is satisfied for each general-purpose application based on the general-purpose OS information obtained by the obtaining unit. The management unit (220), when the condition is verified as being satisfied, places a restriction on the use of the hardware for an applicable general-purpose application in an actual operation phase in which the real-time application and the plurality of general-purpose applications are executed.

Abstract: Techniques are described herein for training a machine learning model and using the trained machine learning model to more accurately determine alignments between matching/corresponding nodes of predecessor and successor graphs representing predecessor and successor source code snippets. A method includes: obtaining a first abstract syntax tree that represents a predecessor source code snippet and a second abstract syntax tree that represents a successor source code snippet; determining a mapping across the first and second abstract syntax trees; obtaining a first control-flow graph that represents the predecessor source code snippet and a second control-flow graph that represents the successor source code snippet; aligning blocks in the first control-flow graph with blocks in the second control-flow graph; and applying the aligned blocks as inputs across a trained machine learning model to generate an alignment of nodes in the first abstract syntax tree with nodes in the second abstract syntax tree.

Abstract: A computing system includes a processor and a memory storing instructions for a compiler that, when executed by the processor, cause the processor to generate a control flow graph of program source code by receiving the program source code in the compiler, in the compiler, generating a structure point representation based on the received program source code by inserting into the program source code a set of structure points including an anchor structure point and a join structure point associated with the anchor structure point, and based on the structure point representation, generating the control flow graph including a plurality of blocks each representing a portion of the program source code. In the control flow graph, a block A between the anchor structure point and the join structure point post-dominates each of the one or more divergent branches between the anchor structure point and the join structure point.

Abstract: This disclosure relates generally to accelerating development and deployment of enterprise applications where the applications involve both data driven and task driven components in data driven enterprise information technology (IT) systems. The disclosed system is capable of determining components of the application that may be task-driven and/or those components which may be data-driven using inputs such as business use case, data sources and requirements specifications. The system is capable of determining the components that may be developed using task-driven and data-drive paradigms and enables migration of components from the task driven paradigm to the data driven paradigm. Also, the system trains a reinforcement learning (RL) model for facilitating migration of the identified components from the task driven paradigm to the data driven paradigm. The system is further capable of integrating the migrated and existing components to accelerate development and deployment an integrated IT application.

Abstract: A control system includes at least one field device, a first control apparatus, a second control apparatus, a cache server, and a network. The first control apparatus has a first field device directly connected thereto and includes a first access route controller and a first control application capable of controlling the first field device. The second control apparatus includes a second access route controller and a second control application capable of controlling the first field device. The cache server includes a memory and a third access route controller. The first through third access route controllers are configured to work together to be capable of transferring, to the cache server, an input/output instruction for the first field device from the second control application.

Abstract: Methods, systems, and computer-readable media are disclosed for dynamic partitioning in distributed computing environments. One method includes: receiving a first data set and a second data set; mapping the first data set into a first set of key-value pairs; mapping the second data set into a second set of key-value pairs; estimating, using a sketch, a frequency count for each key based on the first set of key-value pairs and the second set of key-value pairs; determining whether the estimated frequency count for each key is greater than or equal to a predetermined threshold; and partitioning the key when the estimated frequency count for the key is greater than or equal to the predetermined threshold.

Abstract: A framework, method, and system for generating asynchronous code from state machines coded in a synchronous manner are described. The code is pre-processed into asynchronous code based on the framework prior to compilation thereof. The framework may include various structures and functions such as a save structure, a reentry function, a block wrapping function and a yield identification function.

Abstract: When a process of writing an update program distributed from a management center ends normally during a program update process, a communication adapter executes a restart process by the update program, while retaining a program executed before the program update process. A process of verifying communication between the communication adapter and the management center is automatically executed in a state in which the update program is in execution. When the communication is normal, the program update process is ended.