Abstract: A method includes receiving, by a processing device, first data generated by a first sensor of a substrate processing system. The first data is generated responsive to the first sensor receiving electromagnetic radiation from a substrate held by a robot arm of a transfer chamber in the substrate processing system. The method further includes processing the first data to obtain second data. The second data includes a first indication of performance of the substrate processing system. The method further includes causing, in view of the second data, performance of a corrective actions associated with the substrate processing system.

Abstract: A computer implemented method transforms data. Responsive to receiving a data transformation of an input string to an output string, a computer system identifies mappable tokens in the input string that are mappable to the output string. The computer system creates a set of initial mappings for a set of common tokens in the mappable tokens. The set of initial mappings maps the set of common tokens from the input string to the output string. The computer system creates a set of user mappings that maps the mappable tokens from input string to the output string using a user input to the set of initial mappings. The computer system generates program code that transform input strings to output strings using the set of user mappings that maps the mappable tokens from input string to the output string, wherein the program code is used to transform input strings to output strings.

Abstract: Methods and apparatus for providing query suggestions to a user based on one or more past queries submitted by the user. Candidate query suggestions responsive to a current query may be identified. A candidate query similarity measure may be determined for a given candidate query suggestion based on matching entities related to the given candidate query suggestion and the one or more past queries. In some implementations, the similarity measure of the given candidate query suggestion may be based on a comparison of current entities of the given candidate query suggestion that match entities of one or more past queries, to a group of the current entities that includes entities that do not match the entities of one or more past queries. In some implementations a ranking of the candidate query suggestions may be determined based on the similarity measure.

Abstract: A method, computer program, and computer system are provided for data facet generation. Data associated with a dataset is received. The received data includes one or more data entries having one or more elements. The one or more elements are associated with one or more data types. One or more data facets are generated for each of the data entries with the received data based on the associated data type. One or more transformations are generated for the data facet corresponding to a machine learning task associated with the dataset. A recommendation is provided to a user based on the generated transformation. The provided recommendation includes generated computer code corresponding to an optimal transformation associated with the machine learning task.

Abstract: An interface circuit that can operate in toggle mode at data high transfer rates while reducing the self-induced noise is presented. The high speed toggle mode interface supplies a data signal to a data line or other transfer line by a driver circuit. The driver circuit includes a pair of series connected transistors connected between a high supply level and a low supply level, where the data line is supplied from a node between the two transistors. A resistor is connected between one or both of the transistors and one of the supply levels, with a capacitor connected between the low supply level and a node between the resistor and the transistor. The resistor helps to isolate the transistor from the supply level while the capacitor can act as current reservoir to boost the current to the transistor during data transition, reducing the noise seen by the voltage supply.

Abstract: One embodiment provides a method, including: receiving a sample set for training a machine-learning model, wherein the sample set includes a plurality of classes, wherein classes within the plurality of classes have an imbalance in a number of samples; creating an enlarged minority class by generating new samples from the samples within the minority class and adding the new samples to the minority class; selecting subset samples from both the samples within the enlarged minority class and the majority class; weighting each of the subset samples based upon user input defining goals for attributes of a training sample set to be used in training the machine-learning model; and generating, using the neural network, the training sample set by re-running the selecting in view of the weighting.

Abstract: In an approach to improve knowledge content query generation, embodiments identify one or more drift points based on implicit user feedback-based assessment and a user experience to generate one or more knowledge content queries of different complexity from a multi-media file. Further, embodiments adjust a threshold for the one or more drift points to generate different variations of the one or more knowledge content queries and perform iterative refinement on the one or more knowledge queries based on one or more previous iteration evaluations. Additionally, embodiments generate the one or more knowledge content queries in different modalities based on the multi-media file and the threshold for the one or more drift points.

Abstract: In an approach for generating personalized clues for multiple-choice test questions, a processor analyzes one or more multiple-choice test questions to identify one or more concepts required to be understood to correctly answer each multiple-choice test question. A processor generates a dependency graph corresponding to each multiple-choice test question. A processor monitors a user answer the one or more multiple-choice test questions. Responsive to the user answering at least one of the one or more multiple-choice test questions, a processor assesses whether the user answered the at least one of the one or more multiple-choice test questions correctly. A processor generates a known concept database for the user. Responsive to determining the user is answering a second multiple-choice test question, a processor generates at least one personalized clue based on the dependency graph and the known concept database. A processor presents the user with the at least one personalized clue.

Abstract: A computer-implemented method, a computer program product, and a computer system for automated model lineage inference. A computer system identifies training datasets which is used to train a machine learning model. A computer system identifies parent datasets from which the training datasets are derived. A computer system identifies associated feature transformations when the training datasets are derived from the parent datasets.

Abstract: A system may include a memory and a processor in communication with the memory. The processor may be configured to perform operations. The operations may include extracting a first multiple dimensional dataset and a second multiple dimensional dataset and encoding the first multiple dimensional dataset into a first encoded dataset and the second multiple dimensional dataset into a second encoded dataset. The operations may include combining the first encoded dataset and the second encoded dataset into a combined encoded dataset and conveying the combined encoded dataset to a user.

Abstract: A method and apparatus for providing Web advertisements to online users is disclosed. A balanced set of negative data points and positive data points is derived from a log of Ad impressions and used to train a classifier. In response to an Ad request signal, a plurality of Ads is retrieved from a database. The Ad request signal indicates a request to provide an Ad for a slot available on a Web page associated with a website. The signal is provided in relation to an access of the Web page by an online user and includes information related to the online user. A choice of an Ad is predicted based on the information related to the online user and the plurality of Ads. The Ad is provided to a Web server to cause display of the Ad on the slot when the Web page is displayed to the online user.

Abstract: Techniques are disclosed for providing a notification that a person is at a particular location. For example, a resident device may receive from a user device an image that shows a face of a first person, the image being captured by a first camera of the user device. The resident device may also receive, from another device having a second camera, a second image showing a portion of a face of a second person, the second camera having a viewable area showing a particular location. The resident device may determine a score indicating a level of similarity between a first set of characteristics associated with the face of the first person and a second set of characteristics associated with the face of a second person. The resident device may then provide to the user device a notification based on determining the score.

Abstract: A computer implemented method, computer system, and computer program product for transforming mapped data fields of enterprise applications. A number of processor units receiving a matching from a source data field to a target data field. The set of processor units receiving a number of annotated examples of transformations from a source format to a target format. Based on the annotated examples, the set of processor units autogenerating a query language expression for transforming data items from the source format to the target format.

Abstract: One embodiment provides a method, including: receiving a sample set for training a machine-learning model, wherein the sample set includes a plurality of classes, wherein classes within the plurality of classes have an imbalance in a number of samples; creating an enlarged minority class by generating new samples from the samples within the minority class and adding the new samples to the minority class; selecting subset samples from both the samples within the enlarged minority class and the majority class; weighting each of the subset samples based upon user input defining goals for attributes of a training sample set to be used in training the machine-learning model; and generating, using the neural network, the training sample set by re-running the selecting in view of the weighting.

Abstract: Methods, systems, and computer program products for automatically improving data annotations by processing annotation properties and user feedback are provided herein. A computer-implemented method includes obtaining data annotation pairs, each comprising an input data annotation in a first format and a corresponding output data annotation in a second format; determining, within at least a portion of the data annotation pairs, one or more non-diffs; identifying, across the at least a portion of data annotation pairs, data annotation properties associated with multiple intents by processing the non-diffs using property-related rules; modifying at least a portion of the data annotation pairs based on the identified data annotation properties; outputting the modified data annotation pairs to at least one user; and generating a final collection of data annotation pairs by processing at least a portion of the modified data annotation pairs and user feedback received in response to the outputting.

Abstract: A method for establishing message priority in network slices based on quality of service (QoS) parameters includes receiving, by a network slice configuration service provider entity and from a network slice management service provider entity, a network slice creation notification message containing at least a QoS profile corresponding to a created network slice, utilizing the QoS profile to derive a service based interface (SBI) message priority (SMP) associated with the network slice, and providing the SMP to a requesting access and mobility management function (AMF) entity in response to receiving a network slice selection request message from the AMF entity, wherein the AMF entity assigns the SMP level value to network traffic directed to the network slice.

Abstract: A gaming device comprises a display, a random number generator, a processor, and a memory storing instructions. When the instructions are executed by the processor, they cause the processor to conduct a base game from which feature games and at least one composite feature game can be triggered, where the composite feature game comprises game play characteristics from a first feature game and a second feature game of the feature games, and the composite feature game comprises a combination of the different game play characteristics. The composite feature game is initiated in response to a composite feature trigger condition being met. The game instances are presented with one or more feature game icon, which are modified in presentation during the game instances in accordance with an associated game play characteristic for a particular instance.

Abstract: A method for resolving priorities among network function (NF) instances includes, at a priority resolver implemented using at least one processor, providing a priority resolution application programming interface (API) that allows NF instances to request priority resolution. The method further includes receiving, via the API and from a plurality of NF instances, requests for priority resolution. The method further includes using a priority resolution algorithm to determine a relative priority for each of the NF instances. The method further includes generating and transmitting to each of the NF instances a priority resolution response including the relative priority determined for the NF instance.

Abstract: Virtual storage arrays consolidate branch data storage at data centers connected via wide area networks. Virtual storage arrays appear to storage clients as local data storage; however, virtual storage arrays actually store data at the data center. The virtual storage arrays overcomes bandwidth and latency limitations of the wide area network by predicting and prefetching storage blocks, which are then cached at the branch location. Virtual storage arrays leverage an understanding of the semantics and structure of high-level data structures associated with storage blocks to predict which storage blocks are likely to be requested by a storage client in the near future. Virtual storage arrays determine the association between requested storage blocks and corresponding high-level data structure entities to predict additional high-level data structure entities that are likely to be accessed. From this, the virtual storage array identifies the additional storage blocks for prefetching.

Abstract: Various apparatuses, systems, methods, and media are disclosed to provide over-voltage protection to a data interface of a multi-protocol memory card that includes a first communication interface and a second communication interface that enable communication using different protocols. An interface voltage protection circuit includes a control circuit configured to receive a first supply voltage for operating the first communication interface. The interface voltage protection circuit further includes a pull-down circuit operatively connected with the control circuit, configured to pull down a voltage at a supply voltage rail of the second communication interface such that a voltage at a plurality of connector terminals of the second communication interface is lower than the first supply voltage.