Abstract: A computer-implemented method for performing natural language-based data integration includes causing execution of a data integration application on a remote device via a network and causing surfacing of a GUI corresponding to the data integration application on a display of the remote device. The method includes receiving, via the GUI, a natural language input representing a data integration task, generating, via an LLM, a set of ordered activities corresponding to the data integration task represented by the natural language input, and selecting, via the LLM, one or more APIs for performing each activity within the set of ordered activities. The method also includes generating a data pipeline based on the set of ordered activities and the API(s) for performing each activity, as well as back-translating the data pipeline to a desired data format for execution by the data integration application.

Abstract: Some embodiments generate prompts and submit them in queries to a language model trained on code to perform automated program repair. Some embodiments fix syntactic mistakes and semantic mistakes by combining multimodal prompts, iterative querying, test-case-based selection of few-shots, and program chunking. In some cases, edit distance is minimized between an initial flawed program and the automatically created improved version of that program. The initial flawed program is obtained from a programming student, or from a source code generator.

Abstract: Methods and systems for generating training data for sequential conversational responses to alleviate the collection burden are disclosed herein. More specifically, the methods and systems describe generating determining dynamic conversational responses to generate training data for sequential conversation responses. For example, the system creates a special form of a random treatment control experiment to reduce the data collection while at the same time generating effectively adequate learning data for intents for the sequenced machine learning.

Abstract: A piezoelectric thin film having better FoM and piezoelectric strain constant, a manufacturing apparatus and manufacturing method, and a fatigue estimation system using the film; wherein, the piezoelectric thin film is made of (MgHf)xAl1-xN in which Mg and Hf are co-doped into the Al site of AlN, where x is 0.3 or more and 0.49 or less, and has a figure of merit (FoM) of 45 GPa or more and a piezoelectric strain constant (d33) of 18 pm/V or more. Multiple first pieces made of Mg and multiple second pieces made of Hf are on the surface of a target made of AlN wherein an average surface area of each first piece is 0.9 to 1.1 times an average surface area of each second piece with respect to a surface area of the target, and a piezoelectric thin film is grown on a substrate by magnetron sputtering.

Abstract: Techniques are described herein that are capable of creating a language-agnostic computer program repair engine generator. A context-free grammar is annotated to identify token(s) that are likely to be included in or excluded from a computer program in a manner that violates the context-free grammar. A language-agnostic computer program repair engine generator is created that is configured to generate a parser. The repair engine generator is configured to create a repair engine that: converts the candidate string into repaired strings that neither violate the context-free grammar nor violate a criterion for a valid computer program; calculates differences between the candidate string and the respective repaired strings; and replaces the candidate string with a designated repaired string based at least in part on the difference between the designated repaired string and the candidate string being less than or equal to a difference threshold.

Abstract: Methods and systems are described for generating dynamic interface options using machine learning models. The dynamic interface options may be generated in real time and reflect the likely goals and/or intents of a user. The machine learning model may provide these features by interpreting multi-modal feature inputs. For example, the machine learning model may include a first machine learning model, wherein the first machine learning model comprises a convolutional neural network, and a second machine learning model, wherein the second machine learning model performs a Weight of Evidence (WOE) analysis.

Abstract: Improved cushioning elements for sports apparel, in particular for soles for sports shoes, are described. A cushioning element for sports apparel with a first deformation element is provided. The deformation element includes a plurality of randomly arranged particles of an expanded material, wherein there are first voids within the particles and/or between the particles.

Abstract: A computer-implemented method for performing natural language-based data integration includes causing execution of a data integration application on a remote device via a network and causing surfacing of a GUI corresponding to the data integration application on a display of the remote device. The method includes receiving, via the GUI, a natural language input representing a data integration task, generating, via an LLM, a set of ordered activities corresponding to the data integration task represented by the natural language input, and selecting, via the LLM, one or more APIs for performing each activity within the set of ordered activities. The method also includes generating a data pipeline based on the set of ordered activities and the API(s) for performing each activity, as well as back-translating the data pipeline to a desired data format for execution by the data integration application.

Abstract: Described are methods for the manufacture of a plastic component, in particular a cushioning element for sports apparel, a plastic component manufactured with such a method, for example a sole or a part of a sole for a shoe, and a shoe with such a sole. According to an aspect of the invention, a method for the manufacture of a plastic component, in particular a cushioning element for sports apparel, is provided which includes loading a mold with a first material which includes particles of an expanded material, and, during loading the mold, pre-heating the particles by supplying energy, wherein the energy is supplied in the form of at least one electromagnetic field.

Abstract: A method for monitoring an energy supply of a motor vehicle. At least one supply path is provided, which supplies a safety-relevant, consumer with electrical energy. The supply path includes at least two parallel-connected current-carrying components, in particular a switch and/or fuse, protecting the consumer. At least one electrical characteristic variable, in particular a measure of an electrical resistance, describing the functionality of the supply path is ascertained. At least one electrical measured variable is sensed, which is applied to at least one of the components. As a function of the measured variable, the electrical characteristic variable (R) is determined. A check of at least the electrical characteristic variable takes place. The current-carrying components and the supply path are arranged at least partially in a control unit.

Abstract: Some embodiments perform fully unsupervised string error detection and repair, for strings containing both syntactic errors and semantic errors. In some embodiments, string error mitigation includes learning a regular-expression-based pattern that characterizes at least a predefined fraction of a set of string data values, identifying and masking a semantic substring, deriving edits to repair a string which contains the semantic substring, and replacing a mask value with a replacement substring that conforms to the pattern. Some embodiments utilize a language model. Some embodiments include or utilize a pattern learner, one or more learned significant patterns, and a repair engine. Some embodiments exploit program execution information to generate patterns when significant patterns are not initially found.

Abstract: Various embodiments relate generally to data science and data analysis, computer software and systems, and wired and wireless network communications to provide an interface between repositories of disparate datasets and computing machine-based entities that seek access to the datasets, and, more specifically, to a computing and data storage platform that facilitates consolidation of one or more datasets, whereby a collaborative data layer and associated logic facilitate, for example, efficient access to, and implementation of, collaborative datasets. In some examples, a system may include an atomized workflow loader configured to receive an atomized dataset to load into a data store, and to determine resource requirements data to describe at least one resource requirement. The atomized workflow loader may be further configured to select a data store type based on a resource requirement, and perform a load operation of the atomized dataset as a function of the data store type.

Abstract: Methods and systems are described for generating dynamic interface options using machine learning models. The dynamic interface options may be generated in real time and reflect the likely goals and/or intents of a user. The machine learning model may provide these features by interpreting multi-modal feature inputs. For example, the machine learning model may include a first machine learning model, wherein the first machine learning model comprises a convolutional neural network, and a second machine learning model, wherein the second machine learning model performs a Weight of Evidence (WOE) analysis.

Abstract: A safety-oriented control unit and method for synchronizing measurement values delivered in an individual measurement phase, wherein the measurement values are processed by the safety-oriented controller in a monitoring phase in accordance with a safety function, where individual counter increments of the measurement values are compared with one another in comparison during a current monitoring cycle of the monitoring phase with a previous monitoring cycle, a maximum counter increment is determined, the measurement values that do not have the maximum counter increment are adjusted based on the maximum counter increment, and where at least one monitoring value is established by the safety function based on the adjusted measurement value(s) and the measurement value(s) associated with the maximum counter increment.

Abstract: Improved soles for shoes, in particular sports shoes, are described. A sole for a shoe, in particular a sports shoe, is provided that includes a midsole with randomly arranged particles of an expanded material. The sole further includes an element having a higher deformation stiffness in at least one direction than the expanded material. The material of the midsole at least partially surrounds the element.

Abstract: Described are methods and systems are for generating dynamic conversational queries. For example, as opposed to being a simply reactive system, the methods and systems herein provide means for actively determining a user's intent and generating a dynamic query based on the determined user intent. Moreover, these methods and systems generate these queries in a conversational environment.

Abstract: Systems and techniques are provided for coding video data based on an optical flow correction and a residual correction. For example, a decoding device can obtain a frame of encoded video data associated with an input frame, the frame of encoded video data including an optical flow correction and a residual correction. A predicted optical flow can be generated based on one or more reference frames and a reference optical flow. A corrected prediction frame can be generated based on the predicted optical flow and the optical flow correction. A predicted residual can be generated based on at least the corrected prediction frame and a first reference frame included in the one or more reference frames. The decoding device can generate a reconstructed input frame based on the corrected prediction frame, the predicted residual, and the residual correction.

Abstract: Described are methods for the manufacture of a plastic component, in particular a cushioning element for sports apparel, a plastic component manufactured with such a method, for example a sole or a part of a sole for a shoe, and a shoe with such a sole. According to an aspect of the invention, a method for the manufacture of a plastic component, in particular a cushioning element for sports apparel, is provided which includes loading a mold with a first material which includes particles of an expanded material, and, during loading the mold, pre-heating the particles by supplying energy, wherein the energy is supplied in the form of at least one electromagnetic field.

Abstract: Described are methods for manufacturing a plastic component, in particular a cushioning element for sports apparel, a plastic component manufactured with such methods, for example a sole or a part of a sole for a shoe, and a shoe with such a sole. The method for the manufacture of a plastic component includes loading a mold with a first material includes particles of an expanded material and fusing the surfaces of the particles by supplying energy. The energy is supplied in the form of at least one electromagnetic field.

Abstract: A method and system based on machine learning to create self-adapting analog circuits adapted to change their internal components on-the-fly in response to changes in process, voltage, and temperature to re-tune the electrical characteristics back to nominal specified values is disclose. The method and system herein comprise of designing the analog circuit, generating simulation data for machine learning, creating a full query database, creating and training, using simulation results, a machine learning (ML) model of the circuit and applying the ML model to infer the required changes to internal components of the analog circuit in response to changes in P, V, and T conditions. With this method and system, evaluation of the adverse effects of PVT changes, decision on internal circuit changes, and realization of requisite design changes are performed by the computer system solely within a ML data domain, in a time and resource efficient manner.