Abstract: In industrial inspection scenarios, early detection of machine malfunction is extremely essential as it helps in preventing any significant damage and the associated economic losses. Embodiments herein provide a method and system for an acoustic based anomaly detection in industrial machines using a beamforming and a sequential transform learning. Herein, the system employs two-stage multi-channel source separation technique that uses the well-known delay and sum beamforming followed by a recent data-driven sequential transform learning (STL) approach to obtain clean sources. The STL is a solution to linear state-space model where operators/matrices are learnt from data and is used here to model the dynamics of time-varying source signals for source separation. Subsequently, a reference template matching is employed on each separated source to detect an anomaly.

Abstract: Methods, apparatus, and processor-readable storage media for localized anomaly detection in digital documents are provided herein. An example computer-implemented method includes identifying at least one image in a digital document; processing the identified at least one image using at least an image compression algorithm; applying a first machine learning model to the at least one processed image, wherein the first machine learning model is trained to detect whether the at least one image comprises one or more modifications; in response to detecting that the at least one image comprises at least one modification, applying a second machine learning model to identify a location in the at least one image corresponding to the at least one modification; and generating an indication that identifies the location of the at least one modification in the at least one image.

Abstract: Methods, apparatus, and processor-readable storage media for automated request processing using an ensemble machine learning framework are provided herein. An example computer-implemented method includes aggregating interaction data associated with a request; computing a weighted score for the request, wherein the weighted score comprises a first component that is based at least in part on a comparison of the aggregated interaction data to a set of keywords and a second component corresponding to a sentiment predicted by a first machine learning model for at least a portion of the aggregated interaction data; using a second machine learning model to determine whether the request is anomalous based at least in part on the weighted score; and in response to determining that the request is anomalous, initiating one or more automated actions for the request.

Abstract: Methods, apparatus, and processor-readable storage media for character-based representation learning for table data extraction using artificial intelligence techniques are provided herein.

Abstract: Techniques described herein relate to a method for generating address recommendations. The method includes obtaining, by a recommendation system, an address recommendation request associated with an address, wherein the address is associated with a user; in response to obtaining the address recommendation request: generating a context vector associated with the address; generating an address recommendation based on the context vector using a recommendation model; obtaining user feedback associated with the address recommendation; generating a reward based on the user feedback; and updating the recommendation model based on the context vector, the address recommendation and the reward.

Abstract: A method is disclosed for handling delivery of network-delivered services to a user equipment, UE, in a wireless communication network. The method is performed by at least one network node in the wireless communication network. The method includes receiving a service request associated with a network-delivered service from the UE. The method includes notifying one or more service plans related the service request to the UE, in response to the service request. The method includes receiving a user selection order from the UE, wherein the user selection order identifies a selection of at least one of the one or more service plans from the one or more service plans. Further, the method includes initiating the network-delivered service in accordance with the user selection order. Corresponding network node, user equipment and computer program product are also disclosed.

Abstract: This application relates to apparatus and methods for the monitoring of nodes within datacenters. In some examples, a computing device, such as a node, receives a monitoring file from a monitoring server, where the monitoring file includes a plurality of node health checks. The computing device is configured to execute the monitoring file based on a type of the computing device. Further, and based on the execution of the monitoring file, the computing device is configured to determine that at least one of the plurality of node health checks failed. In response to determining that the at least one of the plurality of node health checks failed, the computing device is configured to generate an alert message identifying the node health checks that failed. Further, the computing device is configured to transmit the alert message to the monitoring server for display.

Abstract: A system according to various embodiments manages user interactions with a helpdesk. The system determines a user satisfaction quota for a user based on an aggregate frequency with which the user called the helpdesk. The helpdesk receives a new call from the user. The new call is answered by an agent of the helpdesk. The system determines a recent interaction score and compares the recent interaction score with the user satisfaction quota for the user. If the system determines based on the comparison, whether the user is a dissatisfied user. If the user is marked as a dissatisfied user, the system generates a summary of a context identifying factors likely to contribute to dissatisfaction of the user and sends the summary of the context for presentation the agent of the helpdesk.

Abstract: Examples described herein include virtualized file servers which may include cloned instances of the virtualized file server. Cloning a virtualized the server may allow for testing of new and/or revised features, disaster recovery plans, or other configurations while maintaining availability of the parent (e.g., source) virtualized file server.

Abstract: Systems and methods for performing single I/O writes are provided. According to one embodiment, responsive to receipt of a write operation from a client by a file system layer of a node of a distributed storage system and a data payload of the operation having been determined to meet a compressibility threshold, an intermediate storage layer of the node logically interposed between the file system layer and a block storage media is caused to perform a single input/output (I/O) write operation that persists the compressed data payload and corresponding metadata to support asynchronous journaling of the write operation. The single I/O write operation coupled with the use of a new pool file that maintains a list of available blocks for single I/O write operations and a modified node crash recovery approach allows the write operation to be acknowledged to the client while the journaling is performed asynchronously.

Abstract: The present invention relates to microbial safety of meat products. In particular new additives are provided for effective reduction of pathogenic bacteria, such as Shiga toxin producing Escherichia coli (STEC), on or in meat products. The present inventors found that a combination of a nonionic surfactant and organic acid is particularly effective in the reduction of these and other pathogenic bacteria in meat products. The addition of a thickening agent was found to further enhance the effectiveness of the compositions in eliminating these pathogenic bacteria. The present invention provides these meat preservation compositions, the methods of treating meat with these compositions, the related uses of these compositions, as well as the meat products accordingly obtained.

Abstract: Examples of systems described herein include a virtualized file servers. Examples of virtualized file servers described herein may support disaster recovery of the virtualized file server. Accordingly, examples of virtualized file servers may support metadata fixing procedures to update metadata in a recovery setting. Examples of virtualized file servers may support hypervisor-agnostic disaster recovery.

Abstract: The present invention relates to microbial safety of meat products. In particular new additives are provided for effective reduction of pathogenic bacteria, such as Shiga toxin producing Escherichia coli (STEC), on or in meat products. The present inventors found that a combination of a nonionic surfactant and organic acid is particularly effective in the reduction of these and other pathogenic bacteria in meat products. The addition of a thickening agent was found to further enhance the effectiveness of the compositions in eliminating these pathogenic bacteria. The present invention provides these meat preservation compositions, the methods of treating meat with these compositions, the related uses of these compositions, as well as the meat products accordingly obtained.

Abstract: The present disclosure involves systems, software, and computer implemented methods for an artificial intelligence work center for ERP data. One example method includes receiving scenario and model settings for an artificial intelligence model for a predictive scenario. A copy of the dataset is processed based on settings to generate a prepared dataset that is provided with the settings to a predictive analytical library. A trained model trained and evaluation data for the trained model is received from the predictive analytical library. A request is received to generate a prediction for the predictive scenario for a target field for a record of the dataset. The record of the dataset is provided to the trained model and a prediction for the target field for the record the dataset is received from the model. The prediction is included for presentation in a user interface that displays information from the dataset.

Abstract: Methods, systems, and devices for wireless communications are described. A distributed unit (DU) component/function of a base station may determine, for one or more radio units associated with the distributed unit, one or more sampling metrics associated with signal combining operations at the radio units. The DU may select, based at least in part on the one or more sampling metrics, a combining scheme to use for the signal combining operations. The DU may provide an indication of the selected combining scheme to at least one radio unit of the one or more radio units.

Abstract: Systems, methods, and computer program products are provided herein for hyperspectral imaging based authentication. An example method includes receiving check data associated with at least a first user and extracting one or more field details from the check data. By leveraging a hyperspectral imaging module, the method further includes generating hyperspectral image data associated with the one or more extracted field details and determining one or more spectral characteristics associated with the one or more extracted field details based on the hyperspectral image data. The method further includes determining a tampering indication for the check data based on the one or more spectral characteristics. The spectral characteristics may include one or more reflectance values associated with extracted field details across a plurality of spectral bands.

Abstract: First images that are screenshots from a first version of a software component are obtained. Second images that are screenshots from a second version are obtained. A collection of image deviations that includes pair-wise image deviations between pairs of images are identified. A pair of images includes a first image from the first images and a corresponding second image from the second images. An image deviation indicates a portion of the second image identified as differing from a spatially corresponding portion of the first image. The image deviations are grouped into deviation groups. At least some of the second images are associated with at least some of the deviation groups. A subset of the second images corresponding to a deviation group is output responsive to a selection of an indication of the deviation group.

Abstract: A machine learning model trained with a triplet loss function classifies input strings into one of multiple hierarchical categories. The machine learning model is pre-trained using masking language modeling on a corpus of unlabeled strings. The machine learning module includes an attention-based bi-directional transformer layer. Following initial training, the machine learning model is refined by additional training with a loss function that includes cross-entropy loss and triplet loss. This provides a deep learning solution to classify input strings into one or more hierarchical categories. Embeddings generated from inputs to the machine learning model capture language similarities that can be visualized in a cartesian plane where strings with similar meanings are grouped together.

Abstract: The present invention relates to a cost effective and single step process for rapid manufacturing of paper-based SERS substrates (100), wherein chitosan is used for direct in situ reduction of the metallic precursor solutions for production of metallic nanoparticles on the substrates. The crucial step in the process involves the incubation of the paper-based substrates under humidifying conditions at an elevated temperature for a predetermined duration. The metal nanoparticles thus produced are homogenously deposited over the paper-based substrate making the paper-based substrate suitable for SERS analysis. The paper-based substrate thus developed is cost-effective, flexible, easy to load and is demonstrated to have exceptional sensitivity with detection limits of up to 1 pM.

Abstract: A temperature sensor includes a sensing element and a load. Multiple different currents pass through the sensing element in a sequential manner. Based on each current that passes through the sensing element, the sensing element outputs a complementary-to-absolute-temperature (CTAT) voltage and another current. Further, the currents that pass through the sensing element and the currents that the sensing element output separately pass through the load and result in the generation of multiple load voltages across the load. A current density ratio of the temperature sensor is determined based on the load voltages generated across the load. Further, a temperature value indicative of a temperature sensed by the temperature sensor is generated based on the current density ratio and the CTAT voltages outputted by the sensing element based on the different currents that pass therethrough.