Abstract: Methods, systems, and devices for data management are described. The initiation or forthcoming initiation of a data protection operation for a computing system may be identified. Short-term information of the computing system, including information stored in the volatile memory of the computing system, network traffic associated with the computing system, or both, may be obtained based on the initiation or forthcoming initiation of the data protection operation. Long-term information of the computing system, including information stored in the non-volatile memory of the computing system, may be obtained based on the data protection operation being initiated. Both the short-term information and the long-term information may be stored for further analysis.

Abstract: A system and a method for passive liveness detection is provided. The system may be configured to identify a color composition of an iris of a user. The system may further generate an adoptive color pattern on a display of a user device based on the identified color composition. Furthermore, the system may capture a reflected color pattern corresponding to the generated adoptive color pattern from the iris of the user. The system may further determine a rate of change of pattern associated with the generated adoptive color pattern and the reflected color pattern to calculate a liveness score. Based on at least the calculated liveness score, the system may determine a verification status of the user.

Abstract: Methods, systems, and devices for data management are described. A query execution module may obtain a first query to interact with a database, and then may compare a first fingerprint associated with the first query (e.g., a unique identifier of the first query) with a set of fingerprints in a fingerprint database. The set of fingerprints in the fingerprint database may correspond to one or more respective queries that are associated with an execution restriction by the database. In some aspects, the execution restriction may be based on execution details of the respective queries, including a length of time taken to execute a query, a quantity of failed executions of the query, among other details. The query execution module may then control an execution of the first query based on whether the first fingerprint has a corresponding matching fingerprint to at least one of the fingerprints in the fingerprint database.

Abstract: A storage appliance or system may support backup and recovery for virtual machines that support various applications. The storage appliance or system may process a backup snapshot of the virtual machine to identify security vulnerabilities in the virtual machine. The storage appliance may generate an index of software packages installed on the virtual machine and software versions of the software packages. The index of software packages may be compared to a list of security vulnerabilities to identify the security vulnerability at the virtual machine. A notification may be triggered, and the notification may indicate a result of comparing the index of software packages and the software versions to the list of vulnerabilities. In some examples, a set of network configurations implemented by the virtual machines may be determined by processing the backup snapshot and used to identify security vulnerabilities.

Abstract: A system and a method for synthetic data generation is provided. The system may be configured to apply a set of transformations on primary data to obtain a latent space. The latent space may be indicative of a relative distribution of a set of features in the primary data. The system may be further configured to generate a set of samples based on sampling performed on the latent space. Furthermore, the system may generate secondary data based on at least the set of samples and a defined input. The defined input may be associated with a number of data points required in the synthetic data. The system may further generate the synthetic data by use of a loss function calculated based on the secondary data and the primary data. Moreover, the system may store the synthetic data in a database.

Abstract: In apparel search context, process of finding a similar item out of thousands of other items is a cumbersome and computationally heavy process. In order to build a deep learning model that can perform the similarity search, hundreds of training images per Stock Keeping Unit (SKU) are required. Due to shortage of training data, this approach fails to generate a deep learning model that can perform the similarity search in intended manner. The existing approaches may also require domain experts to perform classification of apparels, so as to generate the training data. The method and system disclosed herein provide an approach in which positive images and negative images are generated from each query image, which in turn are used for generating a training data. The training data is then used to generate a deep learning model, which is used to perform the similarity search.

Abstract: Methods, systems, and devices for data management are described. The initiation or forthcoming initiation of a data protection operation for a computing system may be identified. Short-term information of the computing system, including information stored in the volatile memory of the computing system, network traffic associated with the computing system, or both, may be obtained based on the initiation or forthcoming initiation of the data protection operation. Long-term information of the computing system, including information stored in the non-volatile memory of the computing system, may be obtained based on the data protection operation being initiated. Both the short-term information and the long-term information may be stored for further analysis.

Abstract: The present invention provides novel fusion proteins comprising two cytokines: interleukin-6 (IL-6) and interleukin-1 beta (IL-1?). Methods of using the fusion proteins to activate target cells or treat a disease are also provided.

Abstract: Planograms are used to create consistency between store locations, to provide proper shelf space allocation, to improve visual merchandising appeal, and to create product-pairing suggestions. Existing solutions do not have a way to accurately estimate the scale of magnification of the object in the shelf image, so unable to distinguish between size variants of the same product. A system and method for facilitating planogram compliance for inventory management in a retail store have been provided. The scales are calculated with use of a vector convergence technique followed by a center clustering which automatically removes outliers. Initially disclosure comprises calculation of scales and centers, then generation of region proposals using those scales and centers, Next, classification of the regions proposed and generation of similarity scores, and on the basis of similarity scores conflict resolution is performed among overlapped region proposals using non-maximal suppression.

Abstract: A storage appliance or system may support backup and recovery for virtual machines that support various applications. The storage appliance or system may process a backup snapshot of the virtual machine to identify security vulnerabilities in the virtual machine. The storage appliance may generate an index of software packages installed on the virtual machine and software versions of the software packages. The index of software packages may be compared to a list of security vulnerabilities to identify the security vulnerability at the virtual machine. A notification may be triggered, and the notification may indicate a result of comparing the index of software packages and the software versions to the list of vulnerabilities. In some examples, a set of network configurations implemented by the virtual machines may be determined by processing the backup snapshot and used to identify security vulnerabilities.

Abstract: Examples of a data migration system are provided. The system may receive a data migration requirement. The system may sort the data stored in the on-premise data warehouse into a plurality of data domains. The system may map the plurality of data domains to a usage parameter index and a storage parameter index to determine a data usage pattern and a data storage pattern. The system may evaluate the data storage pattern and the data usage pattern to determine a data assessment index. The system may determine a data migration index from mapping a plurality of cloud platforms to the data assessment index. The system may determine a data migration model compatible with the data assessment index. The system may generate a data migration output comprising the layout for transferring data stored in the on-premise data warehouse to a compatible cloud platform to resolve the data migration requirement.

Abstract: Examples of a data migration system are provided. The system may receive a data migration requirement. The system may sort the data stored in the on-premise data warehouse into a plurality of data domains. The system may map the plurality of data domains to a usage parameter index and a storage parameter index to determine a data usage pattern and a data storage pattern. The system may evaluate the data storage pattern and the data usage pattern to determine a data assessment index. The system may determine a data migration index from mapping a plurality of cloud platforms to the data assessment index. The system may determine a data migration model compatible with the data assessment index. The system may generate a data migration output comprising the layout for transferring data stored in the on-premise data warehouse to a compatible cloud platform to resolve the data migration requirement.