Abstract: A method and system provides for asynchronous two-way binding between a user interface and a data model which are implemented on different frameworks. The system includes data, data model, and bridge controllers. The data controller provides a front-end binding framework that interacts with a user interface of a user device to manage a bindable property or method for a view on the user device. The data model controller provides a back-end binding framework that manages a data model, the front-end binding framework and the back-end binding framework being different types of frameworks. The bridge controller implements asynchronous two-way binding for the bindable property or method between the front-end binding framework and the back-end binding framework to update the bindable property or method in the data model when data changes at the user interface and to update the view on the user device when data changes at the data model.

Abstract: A machine learning apparatus includes a first information acquiring unit that acquires first information including at least one of a shape of a workpiece, a material of the workpiece, a cutting path of a cutting process, a type of a tool, and an amount of wear of the tool; a second information acquiring unit that acquires second information correlated with an evaluation of a burr occurring on the workpiece due to the cutting process; and a learning unit that executes learning processing using a plurality of pieces of the first information and a plurality of pieces of the second information, and generates a learning model that outputs a cutting condition, according to another piece of first information that is different from the plurality of pieces of first information.

Abstract: This application provides a method for training a neural network model and an apparatus. The method includes: obtaining annotation data that is of a service and that is generated by a terminal device in a specified period; training a second neural network model by using the annotation data that is of the service and that is generated in the specified period, to obtain a trained second neural network model; and updating a first neural network model based on the trained second neural network model. In the method, training is performed based on the annotation data generated by the terminal device, so that in an updated first neural network model compared with a universal model, an inference result has a higher confidence level, and a personalized requirement of a user can be better met.

Abstract: A method includes receiving, from one or more sensors associated with manufacturing equipment, current trace data associated with producing, by the manufacturing equipment, a plurality of products. The method further includes performing signal processing to break down the current trace data into a plurality of sets of current component data mapped to corresponding component identifiers. The method further includes providing the plurality of sets of current component data and the corresponding component identifiers as input to a trained machine learning model. The method further includes obtaining, from the trained machine learning model, one or more outputs indicative of predictive data and causing, based on the predictive data, performance of one or more corrective actions associated with the manufacturing equipment.

Abstract: A boom sprayer includes any number of components to treat plants as the boom sprayer travels through a plant field. The components take actions to treat plants or facilitate treating plants. The boom sprayer includes any number of sensors to measure the state of the boom sprayer as the boom sprayer treats plants. The boom sprayer includes a control system to generate actions for the components to treat plants in the field. The control system includes an agent executing a model that functions to improve the performance of the boom sprayer treating plants. Performance improvement can be measured by the sensors of the boom sprayer. The model is an artificial neural network that receives measurements as inputs and generates actions that improve performance as outputs. The artificial neural network is trained using actor-critic reinforcement learning techniques.

Abstract: A method includes obtaining feature generation code from, which is configured to determine features relating to input data. The method further includes obtaining data grouping code, which is configured to generate training data by determining a plurality of data groupings for the features relating to the input data. The method further includes obtaining modeling code, which is derived at least in part by applying one or more machine learning algorithms to the training data. The method further includes applying a model wrapper code to the feature generation code, the data grouping code, and the modeling code to generate a model wrapper and deploying the model wrapper such that the model wrapper may receive a first application programming interface (API) call including an input data value, determine a score relating to the input data value, and send a second API call including the score in response to the first API call.

Abstract: A method and apparatus are disclosed for enhancing operable functionality of input source code files from a software program by identifying a first code snippet and a first library function which generate similar outputs from a shared input by parsing each and every line of code in a candidate code snippet to generate a templatized code snippet data structure for the first code snippet, and then testing the templatized code snippet data structure against extracted library function information to check for similarity of outputs between the first code snippet and the first library function in response to a shared input so that the developer is presented with a library function recommendation which includes the first code snippet, the first library function, and instructions for replacing the first code snippet with the first library function.

Abstract: A graphically based tool and method for generating programming for a fire monitoring system. The locations of existing devices, such as detectors, in a building being monitored, can be visually presented in the context of the building. New devices can be installed, or the location of existing devices changed since all devices report their locations in the building to the tool. Device location information can be combined with building information to create a multi-dimensional representation of parts of the building being monitored.

Abstract: A machine learning device that searches for a first parameter of a component of a servo control device that controls a servo motor includes: a solution detection unit that acquires a set of evaluation function values used during machine learning or after machine learning, plots the set of evaluation function values in a search range of the first parameter or a second parameter used for searching for the first parameter, and detects whether a search solution is at an edge of the search range or is in a predetermined range from the edge; and a range changing unit that changes the search range to a new search range of the first parameter or the second parameter based on the estimation made on evaluation function values of an evaluation function expression when the search solution is at the edge of the search range or is in the predetermined range.

Abstract: A portable pesticide application equipment with accurate application, which includes a pesticide tank. Rollers are arranged at the bottom of the pesticide tank. An inclined pesticide guide plate is arranged below the filter. A side connector is arranged at one side of the pesticide tank. The side connector is connected with a long hose. The long hose is connected with a pesticide discharging device. The pesticide discharging device includes a pesticide control box, two sides of which are hinged with a first iron handle and a second iron handle. A first nozzle is connected with the bottom end of the first iron handle while a second nozzle is connected with the bottom end of the second iron handle. The upper end of the first iron handle is inserted into a first support rod while the upper end of the second iron handle is inserted into a second support rod.

Abstract: A machine learning apparatus able to obtaining an optimal shift amount of an assist gas. The machine learning apparatus comprises a state-observation section configured to observe machining condition data included in a machining program given to the laser machine, and measurement data of a dimension of dross generated at a cutting spot of the workpiece when the machining program is executed, as a state variable representing a current state of an environment in which the workpiece is cut; and a learning section configured to learn the shift amount in association with cutting quality of the workpiece, using the state variable.

Abstract: To suppress occurrence of stress corrosion cracking in a weld due to tensile residual stress generated in a web or a middle rib in case of bend forming of an aluminum alloy extrusion having the weld on the web or/and the middle rib. In bend forming of the aluminum alloy extrusion, a peak position of tensile residual stress generated in the middle rib exists in a region other than the vicinity of the weld. Since the peak position is away from the weld by a distance, tensile residual stress in the weld is reduced, making it possible to suppress occurrence of stress corrosion cracking.

Abstract: The invention relates to a method and terminal equipment for planting vegetables on internet rental land, thereby enabling land lessees with idle land to cooperate with urban people seeking to eat green vegetables which are economical and practical, on the one hand, meeting the requirement that urban people eat green vegetables which are practical and reliable, on the other hand, enabling idle land to be reasonably utilized, especially wasting land in rural areas, and bringing considerable benefits to the land lessees; meanwhile, along with the popularization and application of the method and the terminal equipment, a large number of employment posts can be brought to rural areas, and the economic development of the rural areas can be promoted.

Abstract: Disclosed herein are techniques for analyzing hardware change impacts based on at least one functional line-of-code behavior and relation model. Techniques include identifying a new hardware component associated with a system; accessing a first line-of-code behavior and relation model representing execution of functions using the new hardware component; accessing a second line-of-code behavior and relation model representing execution of functions on a previous hardware component of the system; performing a functional differential comparison of the first line-of-code behavior and relation model to the second line-of-code behavior and relation model; determining, based on the functional differential comparison, a status of functional equivalence between the new hardware component and the previous hardware component; and generating, based on the determined difference, a report identifying the status of functional equivalence.

Abstract: For the purpose of reproducing a call stack accurately without restricting the range of application, a stack scanner extracts, from a stack area of a thread whose call stack is to be acquired in a memory space of an application process, possible return addresses that are addresses in a feasible region in the memory space each representing a command right after a function call command. A program analyzer analyzes a control flow representing a flow of control configured by a branch in a function that is called by the function call command right before the command represented by each of the possible return addresses and, when there is a route reaching a command currently being executed in the control flow, determines that the possible return address is a return address and, when there is not the route, determines that the possible return address is not a return address.

Abstract: A wire disconnection prediction device includes: a data acquisition part configured to acquire data relating to machining of a workpiece during machining of the workpiece by a wire electric discharge machine; a preprocessing part configured to create, based on the data acquired by the data acquisition part, machining condition data, machining member data and machining state data, as state data indicating a state of the machining; and a machine learning device configured to execute, based on the state data created by the preprocessing part, processing relating to machine learning using a learning model indicating correlation between a machining state in the wire electric discharge machine and presence/absence of a possibility of disconnection occurrence of a wire electrode in the wire electric discharge machine and a disconnection cause by a plurality of class sets.

Abstract: Systems and methods for generating mobile applications are described. A user interface is provided to enable selecting one or more declaratives to generate a mobile application, wherein the one or more declaratives are used to visually configure characteristics of the mobile application. Data corresponding to selection of one or more declaratives for the mobile application is received. Data corresponding to selection of a layout to associate the one or more selected declaratives with the mobile application is received. Metadata associated with the one or more selected declaratives and metadata associated with the selected layout is determined. A mobile application may be generated at least based on the determined metadata associated with the one or more selected declaratives and with the selected layout.

Abstract: Implementations are described herein for adapting existing source code snippets to new contexts. In various implementations, a command may be detected to incorporate an existing source code snippet into destination source code. An embedding may be generated based on the existing source code snippet, e.g., by processing the existing source code snippet using an encoder. The destination source code may be processed to identify one or more decoder constraints. Subject to the one or more decoder constraints, the embedding may be processed using a decoder to generate a new version of the existing source code snippet that is adapted to the destination source code.

Abstract: Techniques are described with respect to devising a self-movement path for at least one printing device. An associated method includes aggregating environmental datapoints related to at least one environmental parameter associated with a defined printing vicinity of at least one printing device and aggregating printing device datapoints related to at least one printing hardware parameter associated with the at least one printing device. The method further includes, based upon the aggregated environmental datapoints and the aggregated printing device datapoints, configuring a machine learning knowledge model to determine a self-movement path for each of the at least one printing device between a source location of the printing device and a target location of the printing device. The method further includes facilitating creation of the self-movement path for each of the at least one printing device to facilitate processing of an object within the defined printing vicinity.

Abstract: The laser machining system includes a laser device configured to output a laser beam, and a machining head configured to emit the laser beam emitted by a laser oscillator of the laser device and propagated through an optical fiber, to a workpiece in order to perform laser machining. The machining head includes at least one wavelength selective mirror having wavelength selectivity with various values of reflectivity and transmittance according to wavelengths, and at least one image capturing device. The laser machining system monitors abnormality in a laser optical system leading from the laser oscillator to the machining head, during the laser machining, by reflecting light propagated from a side of introduction of the laser beam into the machining head by the wavelength selective mirror, making the light incident on an image capturing surface of the image capturing device, and detecting incident light illuminance distribution appearing on the image capturing surface of the image capturing device.