Abstract: A method includes determining, by a processor of a computing device, a subset of models included in a plurality of models generated based on a genetic algorithm and corresponds to a first epoch of the genetic algorithm. Each of the plurality of models includes data representative of a neural network. The method includes aggregating the subset of models to generate an ensembler. The ensembler, when executed on an input, provides at least a portion of the input to each model of the subset of models to generate a plurality of intermediate outputs. An ensembler output of the ensembler is based on the plurality of intermediate outputs. The method further includes executing the ensembler on input data to determine the ensembler output.

Abstract: A quantum computing service provides a quantum algorithm development kit that enables a customer to define a quantum task, a quantum algorithm, or a quantum circuit using an intermediate representation. The quantum computing service is then configured to automatically translate the quantum task, quantum algorithm, or quantum circuit into a specific representation specific to a particular quantum computing technology selected by the customer to be used to execute the customer's quantum task, quantum algorithm, or quantum circuit.

Abstract: A method for data-centric networked application development includes: modifying a graphical user interface of a networked application development environment with a selectable component for including a reusable data entity in a project, the reusable data entity being defined and bound to a form component via interaction with the graphical user interface; and configuring a block of a data-centric form of the project with the form component in response to selection of the selectable component at a design surface of the graphical user interface.

Abstract: The application provides a processing method and device. Weights and input neurons are quantized respectively, and a weight dictionary, a weight codebook, a neuron dictionary, and a neuron codebook are determined. A computational codebook is determined according to the weight codebook and the neuron codebook. Meanwhile, according to the application, the computational codebook is determined according to two types of quantized data, and the two types of quantized data are combined, which facilitates data processing.

Abstract: As organizations scale analytics, a challenge is the huge increase in number of analytics pipelines to be maintained by developers. In here, lies an example method and modular software architecture to assemble analytics pipeline from reusable components. (1) Reusable components can be utilities where each utility is versioned and has a collection of programming functions, also known as nodes, that follow “data-in-data-out” convention. As nodes are building blocks of a pipeline, an assembly instruction and human readable configurations can now be created to define a project pipeline from a repository of pipelines and well-versioned utilities. (2) By separating out re-usable functionalities from pipelines and data layers, this layered architecture can now support upgrades of functionalities overtime without re-writing of pipelines.

Abstract: The disclosed embodiments combine an energy balance (e.g., averaged energy profiles) with original time series data having smaller time steps to establish an energy balance (e.g., averaged profiles) and a power balance (e.g., smaller time step with original time series data) for a Distributed Energy Resources (DER), microgrid, or other energy system. In an embodiment, a method comprises: solving, with at least one processor, a first optimization problem on time series data related to energy system planning, the first optimization including applying a power balancing framework to the time series data that captures intra-hour variability; and selecting, with the at least one processor, technology assets and sizing for the energy system based on an average hourly and sub-hourly datasets.

Abstract: An online review system determines scores for document authors and document reviewers. An author score is based on a number of comments added to a document by reviewers. One way to compute the author score is to use a ratio of a number of comments provided by reviewers of a document to a number of lines of document contents provided by the author. A reviewer score for a reviewer is based on an amount of comments subsequently made by other reviewers, and on the document content itself, such as a ratio of a number of comments provided in subsequent reviews of a document to a number of lines of original document contents. In some embodiments, the online review system monitors trends in scores of individuals or teams.

Abstract: Systems and methods are directed to controlling components of a utility grid. The system can receive data samples including signals detected at one or more portions of a utility grid. The system can construct a matrix having a first dimension and a second dimension. The system can train a machine learning model based on the matrix to predict values for signals of the utility grid not provided in the matrix. The system can receive bounds for one or more input variables, constraints on one or more output variables, and a performance objective for the utility grid. The system can determine, based on the machine learning model and via an optimization technique, an adjustment to a component of the utility grid that satisfies the performance objective. The system can provide the adjustment to the component of the utility grid to satisfy the performance objective.

Abstract: A method includes: determining, by a computing device, transactions of a monolithic application; ranking, by the computing device, the transactions using predefined rules; selecting, by the computing device, a candidate transaction from the ranked list; determining, by the computing device, lines of application code of the monolithic application associated with the candidate transaction; mapping, by the computing device, respective ones of the determined lines of application code to a first operation and a second operation, wherein the first operation and the second operation are different types of operation; and defining, by the computing device, a target state design based on CQRS (Command Query Responsibility Segregation), the target state design including a first microservice that performs the first operation and a second microservice that performs the second operation.

Abstract: Apparatuses, systems, and techniques to perform a fast Fourier transform operation. In at least one embodiment, a fast Fourier transform operation is performed based on one or more parameters, wherein the one or more parameters indicate information about one or more operands of the fast Fourier transform.

Abstract: A device is further configured to determine a location within a spatial domain for a first program. The device is further configured to determine a first distance threshold value that corresponds with a first distance away from the location of the first program within the spatial domain. The device is further configured to determine distances between the location of the first program and locations of other programs from the plurality of programs and to identify one or more programs from the plurality of programs that are less than the first distance threshold value. The device is further configured to identify the one or more programs from the plurality of programs that are less than the first distance threshold value.

Abstract: Over the past several decades, rapid advances in semiconductors, automation, and control systems have resulted in the adoption of programmable logic controllers (PLCs) in an immense variety of environments. Machine learning techniques help train replacement PLCs when a legacy PLC must be replaced, e.g., due to aging or failure. The techniques facilitate the efficient adoption and correct operation of replacement PLCs in the industrial environment.

Abstract: Methods, systems, and computer readable medium for a multi-source item creation system. The method includes receiving, through a user interface and from a requesting member of a digital platform, manufacturing parameters for an item to be manufactured, dynamically altering the user interface based on the manufacturing parameters to include different user interface elements that correspond to a subset of attributes, determining, based on interaction with the different user interface elements, additional manufacturing parameters, generating, using one or more machine learning models, a set of manufacturers based on the manufacturing parameters and the additional manufacturing parameters, wherein the one or more machine learning models have been trained to generate the set of manufacturers based on a level of uniqueness of the item to be manufactured and characteristics of the manufacturers, and returning, to the requesting member, a subset of the set of manufacturers.

Abstract: A method for reducing idleness in a machine-learning training system can include performing operations by computing devices. A first set of training operations can access and prepare a plurality of training examples of a set of training data. A second set of training operations can train a machine-learned model based at least in part on the set of training data and can include one or more repeat iterations in which at least a portion of the second set of training operations is repeatedly performed such that the training example(s) are repeatedly used to train the machine-learned model. A rate of the repeat iteration(s) can be based at least in part on an echo factor that can be based at least in part on a comparison of a first computational time of the first set of training operations to a second computational time of the second set of training operations.

Abstract: Methods and systems are used for achieving interface design consistency across micro services. As an example, a user interface (UI) training request including at least a set of reference objects is received, the set of reference objects including at least a set of reference UIs. A user interface behavior reference model (UIBRM) is trained to generate a trained UIBRM by analyzing reference UI displays rendered on a browser in response to interactions with the set of reference UIs. A UI displays assessment request including at least a set of development objects is received, the set of development objects including at least a set of development UIs. A UI displays assessment is performed to generate an assessment of development UI displays by comparing the trained UIBRM to the development UI displays rendered on the browser in response to interactions with at least a subset of the set of development UIs.

Abstract: A platform for training deep neural networks using push-to-corner preprocessing and adversarial training. A training engine adds a preprocessing layer before the input data is fed into a deep neural network at the input layer, for pushing the input data further to the corner of its domain.

Abstract: A computerized crop growing management system (CMS) for a farm includes a main controller with an associated user interface (UI). The farm has a plurality of fields on each of which a different crop may be raised, each crop having different irrigation and nutrient requirements. Each field is fed by a main irrigation line connected to a network of irrigation pipes having controller-based valves. Sensors monitor growing conditions in each field. The UI is configured to permit an operator to monitor growing conditions, and control the supply of irrigation liquid and nutrients to each field and/or each crop. The UI allows the operator to specify and create irrigation schedules, nutrient recipes and flow rates, as well as warn an operator of technical and crop problems.

Abstract: A synthesis procedure learns program transformations for a text document, on-the-fly during an edit session, from examples of concrete edits made during the edit session and from an unsupervised set of additional inputs. The additional inputs are derived from explicit feedback from the user and inferred feedback from the user's behavior during the edit session. A reward score, based on anti-unification and provenance analysis, is used to classify the additional inputs as either a positive input or a negative input. Outputs are generated for the positive inputs that are consistent with the existing examples and then used to synthesize a new program transformation. The program transformations are then used to generate code edit suggestions during the edit session.

Abstract: A method is disclosed that includes the operations below: determining, by a processing unit, that arrival times of a lot arrived at N process stages are less than processing times of the lot predetermined to be processed at the N process stages, N being a positive integer; comparing, by the processing unit, idle times of multiple tools in the N process stages; and processing the lot with a first tool of the tools at each one of the N process stages, wherein the first tool of the tools has a shortest idle time.

Abstract: A lexical analyzer is provided to analyze serverless application code to help ensure that the serverless application is portable between different execution environments. The lexical analyzer may identify non-portable features of the application, and alerts of these features may be provided to users. A transfer tool may be provided to assist in transferring a serverless application between computing platforms, such as by converting the portable serverless application to a container format. An interface may be provided that subscribes, on behalf of a container, to receive notifications of triggering events from a computing platform's notification service. The interface may provide a message to the container to indicate an occurrence of a triggering event, which may trigger execution of a serverless function by the container.