Abstract: A method, computer program, and computer system are provided for explaining generation of a flow from natural language utterances. Data corresponding to a natural language utterance is received. One or more constraints corresponding to a flow to be generated are determined based on the received natural language utterance. A flow is constructed based on the determined constraints. An explanation associated with the constructed flow is provided, and the explanation identifies parameters corresponding to constructing the flow.

Abstract: A particle sensor for measuring size and concentration properties of particles in a gas includes a bipolar diffusion charger configured to charge particles within a received gas sample by the collision of the received particles with and transfer of charge from both positive and negative ions concurrently. At least one electrometer detects the charge of received particles thereby charged. The net, positive, negative or total charge on the bipolarly charged particles has a low sensitivity to variations in the absolute rate of charge generation in the bipolar diffusion charger. A sensor for a ratio of ion charge mobilities in a bipolar diffusion charger employs an ion trap between the bipolar diffusion charger and at least one electrometer.

Abstract: A method or system for testing and benchmarking commits made on source code. The system extracts commits from a history of a first code history that records a sequence of commits made thereon. The extracted commits are then combined into a sequence of patches, each of which includes changes made during consecutive commits. The system also establishes a connection with a system under test (SUT) having a second code repository corresponding to a historical version of the first code repository before the extracted commits were made, and sequentially applies the sequence of the patches to the second code repository. Performance of the SUT is monitored during the application of the sequence of the patches to determine whether the SUT performs as expected after the application of each patch.

Abstract: The present disclosure is directed toward systems, methods, and non-transitory computer-readable media for generating context engine outputs by utilizing an interpreter purpose-built to execute code generated by large language models. For example, the disclosed systems generate computer code executable for responding to a query by utilizing a large language model. In addition, the disclosed systems execute the model-generated computer code utilizing an interpreter integrated with the context engine that further includes swappable logic interchangeable across multiple executors. Moreover, the disclosed systems can further generate as part of executing the computer code utilizing the interpreter, a first context engine output by implementing the interpreter at a first executor. Additionally, the disclosed systems can further generate a second context engine output by implementing the interpreter at a second executor.

Abstract: In an approach to improve prompt variations to enhance user-based experiences while interacting with artificial intelligent (AI) systems, embodiments generate variations of the prompts associated with the initial input by automatically leveraging machine learning techniques and collect the prompts from a user resulting from an interaction with an artificial intelligent (AI) system. Further, embodiments, identify a heuristic to organize suggestions and the variations of the prompts, and determine and utilize the heuristic to organize the variations of the prompts in systematic categories to produce an efficient display of the variations of the prompts, in a graphic user interface (GUI), for the user to view. Additionally, embodiments, update the variations of the prompts based on identified interaction data from the user, and dynamically output the updated variations of the prompts in response to the identified and collected user data.

Abstract: An integrated platform system that employ a series of machine learning techniques and prediction and detection units that can process input data and extract and generate meaningful insights and predictions therefrom. The system integrates together multiple different data storage types and applications that generates data of different types, and an associated processing system for processing the different data types, store the data in a common data model to normalize the data, determine the data lineage of the data, and then process the data using different types of techniques. The data can also be processed by a prediction unit for generating meaningful insights and predictions or by an anomaly detection unit for detecting one or more anomalies in the data.

Abstract: A brace assembly for mounting an electrical box between support members, the brace assembly including a hangar body having a first end and a second end, an extension assembly operatively coupled to the first end of the hangar body, the extension assembly being selectively movable between a retracted position and an extended position relative to the hangar body and configured to lock when in the retracted position and when in the extended position, an adjustment member operatively coupled to the extension assembly such that the adjustment member can move axially relative to the extension assembly and a mounting bracket mounted to the brace assembly for releasably mounting the electrical box to the brace assembly.

Abstract: A method or system for testing and benchmarking commits made on source code. The system extracts commits from a history of a first code history that records a sequence of commits made thereon. The extracted commits are then combined into a sequence of patches, each of which includes changes made during consecutive commits. The system also establishes a connection with a system under test (SUT) having a second code repository corresponding to a historical version of the first code repository before the extracted commits were made, and sequentially applies the sequence of the patches to the second code repository. Performance of the SUT is monitored during the application of the sequence of the patches to determine whether the SUT performs as expected after the application of each patch.

Abstract: An enteral feeding tubing connector comprises a body, a bore extending through the body, and a collet slidably disposed in the bore at a first end of the body. The collet is dimensioned to receive and engage a portion of tubing inserted into the collet, and is configured to resist withdrawal of the tubing from the bore and body upon application of force to the tubing that moves the collet out of the bore. A lock is provided on the first end of the body, and is configured to selectively engage the collet and prevent movement of the collet outward relative to the body. A tubing connection is provided at a second, opposite end of the body, the tubing connection providing fluid communication between another portion of tubing, the bore extending through the body, and the portion of tubing inserted into the collet.

Abstract: A mounting assembly is provided for quick and easy attachment to engineered joists. The mounting assembly includes a brace assembly and a mounting bracket. The mounting assembly may also include an electrical box. The brace assembly is an adjustable member that extends between flanges of engineered ceiling joists. The brace assembly has two low profile end caps that can engage the flanges of engineered ceiling joists and apply a force against the flanges when tightened. The mounting bracket is connected to a hanger body of the brace assembly by a snap fit and the electrical box is attached to the mounting bracket.

Abstract: A method of controlling at least one spray head of a crop sprayer includes capturing, as the crop sprayer traverses a field, a color image of an area of the field to be potentially sprayed by a first spray head, dividing at least part of the captured image into a first set of sub-areas, determining whether at least a defined number of the sub-areas corresponding to the first spray head include at least a defined number of pixels having defined color values corresponding to foliage to be sprayed, and activating the first spray head upon at least the defined number of the sub-areas areas corresponding to the first spray head having more than the defined threshold of pixels within the defined color values.

Abstract: A system and method is disclosed for evaluating a plurality of cryptocurrencies, the method comprising monitoring and storing volatility data for a plurality of cryptocurrency exchanges; analyzing the stored volatility data to generate one or more risk forecasts indicating risks associated with purchasing cryptocurrency through each of the cryptocurrency exchanges; determining a number of transaction factors for purchasing cryptocurrencies and selecting a cryptocurrency based on the transaction factors.

Abstract: Provided are techniques for moderating Artificial Intelligence (AI) agent interlocution in group dialog environments. Under control of an interlocution module that has been trained with dialog content and dialog turns, an indication that interlocution is to be determined for a group dialog is received. Under control of the interlocution module, it is determined whether an AI agent is to participate in the group dialog based on a current dialog context and a dialog response. Under control of the interlocution module, in response to determining that the AI agent is to participate in the group dialog, the AI agent is triggered to post the dialog response to the group dialog.

Abstract: A system or a method for analyzing a software project for vulnerabilities. The system extracts scopes of source code, each of which is a source code block that contains a definition of an entity. The system also receives a vulnerability report relating to the source code. The vulnerability report identifies a vulnerability at a line of the source code. The system identifies a subset of the scopes of source code that contains the line of source code where the vulnerability is identified. The system identifies, based on smatch values, a minimum scope among the subset of the scopes that contains the line of source code where the vulnerability is identified, and generates a scoped vulnerability report recording the minimum scope and the vulnerability.

Abstract: A present invention embodiment analyzes user input via natural language processing. A natural language utterance from a user is analyzed to determine one or more computing tasks. the natural language utterance is analyzed using a knowledge base to identify one or more modifications to the natural language utterance that are based on previous user modifications to a previous user utterance. An indication that the user accepted at least one modification of the one or more modifications is received, wherein the at least one modification modifies the one or more computing tasks. The modified one or more computing tasks are executed.

Abstract: A system and method to adaptively generate a program model. Source code of a program to be tested for code issues, and a set of predefined patterns to be tested in the source code are received. Feature configuration data is generated by determining a set of features corresponding to the received set of predefined patterns. A set of program models is identified by selecting, for each feature in the set of features, a program model from among a plurality of program models that is optimized for the feature. A dynamic program model is built based on the identified set of program models, the dynamic program model being adapted to resolve each of the patterns included in the received set of predefined patterns. And the source code is tested for code issues by extracting from the dynamic program model instances of each of the set of predefined patterns.

Abstract: In one aspect, the present disclosure relates to a method which, in one example embodiment, can include reading text data corresponding to messages and creating semantic annotations to the text data to generate annotated messages. Creating the semantic annotations can include generating, at least in part by at least one trained statistical language model, predictive labels as annotations corresponding to language patterns associated with the text data. The method further includes aggregating the annotated messages and storing information associated with the aggregated annotated messages in a message store, and performing, based on information from the message store and associated with the messages, global analytics functions.

Abstract: An integrated platform system that employ a series of machine learning techniques and prediction and detection units that can process input data and extract and generate meaningful insights and predictions therefrom. The system integrates together multiple different data storage types and applications that generates data of different types, and an associated processing system for processing the different data types, store the data in a common data model to normalize the data, determine the data lineage of the data, and then process the data using different types of techniques. The data can also be processed by a prediction unit for generating meaningful insights and predictions or by an anomaly detection unit for detecting one or more anomalies in the data.

Abstract: A system and method to adaptively generate a program model. Source code of a program to be tested for code issues, and a set of predefined patterns to be tested in the source code are received. Feature configuration data is generated by determining a set of features corresponding to the received set of predefined patterns. A set of program models is identified by selecting, for each feature in the set of features, a program model from among a plurality of program models that is optimized for the feature. A dynamic program model is built based on the identified set of program models, the dynamic program model being adapted to resolve each of the patterns included in the received set of predefined patterns. And the source code is tested for code issues by extracting from the dynamic program model instances of each of the set of predefined patterns.