Abstract: A systematic mechanism for visualizing functions or capabilities that an application has. One or more user experience objects are generated corresponding to an application. An application definition is obtained for that application, and then multiple user experience templates are identified based on that application definition. Information from the application definition is then used to populate at least one of the user experience templates to generate at least one object experience object. The user may then review visualizations of the user experience objects to determine the general capabilities of the application, and thereby determine whether to install or open the application, and how best to use the application.

Abstract: The present disclosure relates to systems and methods for carrying out predictive analysis where a plurality of data sets may be ingested from a data lake. A data analyzer may tag the ingested data sets, detect redundant occurrence of multiple attributes such as, a row, a column, and a list in the tagged data set. The data analyzer may eliminate the detected redundant multiple attributes. Further, a model selector and evaluator may execute a machine learning (ML) model to conduct predictive analysis on the data set. The execution may be done based on a predefined set of instructions stored in a database. The executed ML model may be validated upon determining that the predictive analysis yields a positive response for the transformed data set.

Abstract: A method and system for cloud based service provider performance evaluation are disclosed. The method may include extracting service record data and ticket status change record data from the service ticket data and aggregating the service record data and the ticket status change record data. The method may include calculating ticket level performance metric data based on the aggregated record data and generating ticket level performance scores based on the ticket level performance metric data. The method may further include generating service level performance scores based on the service level performance metric data and generating service feedback performance scores based on the service feedback metric data. The method may further include merging the ticket level performance scores, the service level performance scores, and the service feedback performance scores to generate performance vectors and evaluating overall performances of the service providers based on the set of performance vectors.

Abstract: A method of coating a metallic substrate includes immersing a metallic substrate in a polymer composition including a conductive 3,4-ethylene dioxythiophene (EDOT) polymer, a gelatin polyelectrolyte, an antibacterial drug, an organic solvent, and an inorganic salt solute, and further coating the polymer composition onto a surface of the metallic substrate by cyclic voltammetry to form a coating on the surface of the metallic substrate. The coating on the metallic substrate is performed such that the gelatin and the antibacterial drug are uniformly distributed throughout the coating, and the coating has a thickness between 7.0 and 15.0 micrometers. The metallic substrate is a stainless steel (SS). An implantable medical device including a metallic substrate coated by the present method.

Abstract: A multi-layer database sizing stack may generate prescriptive tier requisition tokens for controlling requisition of database-compute resources at database-compute tiers. The input layer of the database sizing stack may obtain historical data. The threading layer may be used to flag occurrences of single threading application execution. The change layer may be used to determine potential for a step based on compute utilization type data and assert flags indicating the potential. The step layer may determine if potential steps may be taken based on operation-rate type data and flush type data. The requisition layer may generate a tier requisition token based on the provisional requisition tokens generated at other layers and/or finalization directives obtained at the requisition layer.

Abstract: Methods, computer systems, and apparatus, including computer programs encoded on computer storage media, for allocating computation resources for a plurality of databases. For each database, the system identifies a respective initial computation capacity tier for the respective database based at least on the respective utilization of the respective database. For each of a set of optimization orders, the system determines a respective set of candidate resource pools for accommodating the plurality of databases. The system selects an optimization order and determines a final set of resource pools for the plurality of databases. The system outputs data specifying the final set of resource pools.

Abstract: A method to form a metal matrix composite reinforced with eggshell (ES). The method includes preparing an ES powder, blending and milling the ES powder with at least one metal powder selected from the group consisting of magnesium (Mg), zirconium (Zr) to form a powder mixture, compacting and sintering the powder mixture to form the metal matrix composite. In addition, a Mg—Zr-ES metal matrix composite with improved corrosion resistance, having an amount of magnesium from 95 to 97 wt. %, an amount of zirconium from 1 to 2 wt. %, and an amount of ES from 1 to 4 wt. %, may be used for biomedical applications.

Abstract: A layered window in thermophotovoltaic (TPV) devices is disclosed herein. The device may include two or more front window layers, including an outer front window layer nearest the light source that is thin and highly doped and a lower doped inner front window layer nearest a TPV absorber layer. In some embodiments, there may be additional front window layers between the outer front window layer and the inner front window layer. In some embodiments, the TPV device also may include a front contact, a back contact, and other components.

Abstract: Methods, computer systems, and apparatus, including computer programs encoded on computer storage media, for training a machine-learning model for predicting event tags. The system obtains event data that specifies, for each of a plurality of events, a respective set of text fields characterizing the respective event. The system generates, from the event data, encoded language features for the plurality of events. The system also obtains knowledge data that specifies information of the event data. The system generates, from the event data and the knowledge data, tag data specifying a respective tag for each of the plurality of events. The system generates, from the tag data and the encoded language features, a respective encoded feature vector for each of the plurality of events. The system combines the tag data with the encoded feature vectors to generate a plurality of training examples.

Abstract: A system includes a multi-layer throughput optimization (TPO) stack to generate a token containing prescriptions for rightsizing database service throughput.

Abstract: A multi-layer elastic requisition stack may generate pool requisition tokens for controlling requisition of pooled database-compute resources. The elastic requisition stack may determine candidate databases for inclusion in elastic pools by analyzing historical utilization data and generating predicted utilization data. Based on the historical and predicted utilization data, the elastic requisition stack may determine multiplexing characteristics for the candidate databases and complement factors among the databases. The elastic requisition stack may compare unpooled database performance to pooled database performance to determine whether to pool the candidate databases.

Abstract: A multi-layer serverless sizing stack may determine a compute sizing correction for a serverless function. The serverless sizing stack may analyze historical data to determine a base compute allocation and compute buffer range. The serverless sizing stack may traverse the compute buffer range in an iterative analysis to determine a compute size for the serverless function to support efficient computational-operation when the serverless function is instantiated.

Abstract: A saltwater corrosion resistant hybrid composite is provided. The saltwater corrosion resistant hybrid composite coating includes at least one conductive polymer, crumb rubber, and a cured epoxy. The conductive polymer is dispersed in particles of the crumb rubber to form a network. The network is dispersed in the cured epoxy to form the saltwater corrosion resistant hybrid composite coating. A method of making of the saltwater corrosion resistant hybrid composite is also provided. A metal when coated with the resistant hybrid composite of the present disclosure is resistant to salt-water corrosion.

Abstract: A method and system for cloud based service provider performance evaluation are disclosed. The method may include extracting service record data and ticket status change record data from the service ticket data and aggregating the service record data and the ticket status change record data. The method may include calculating ticket level performance metric data based on the aggregated record data and generating ticket level performance scores based on the ticket level performance metric data. The method may further include generating service level performance scores based on the service level performance metric data and generating service feedback performance scores based on the service feedback metric data. The method may further include merging the ticket level performance scores, the service level performance scores, and the service feedback performance scores to generate performance vectors and evaluating overall performances of the service providers based on the set of performance vectors.

Abstract: A multi-layer elastic requisition stack may generate pool requisition tokens for controlling requisition of pooled database-compute resources. The elastic requisition stack may determine candidate databases for inclusion in elastic pools by analyzing historical utilization data and generating predicted utilization data. Based on the historical and predicted utilization data, the elastic requisition stack may determine multiplexing characteristics for the candidate databases and complement factors among the databases. The elastic requisition stack may compare unpooled database performance to pooled database performance to determine whether to pool the candidate databases.

Abstract: A multi-layer serverless sizing stack may determine a compute sizing correction for a serverless function. The serverless sizing stack may analyze historical data to determine a base compute allocation and compute buffer range. The serverless sizing stack may traverse the compute buffer range in an iterative analysis to determine a compute size for the serverless function to support efficient computational-operation when the serverless function is instantiated.

Abstract: A saltwater corrosion resistant composite coating is described. The coating includes at least one conductive polymer, chitosan, reduced graphene oxide (rGO), and a cured epoxy. The rGO and chitosan are dispersed in particles of the conductive polymer to form a 3D network. At least a portion of the chitosan is covalently bound to the rGO. At least a portion of the conductive polymer is covalently bound to the chitosan, and the 3D network is dispersed in the cured epoxy.

Abstract: Embodiments of this disclosure disclose a method and system for optimizing resources for cloud-based scalable distributed search data analytics service. The method may include generating a computing capacity rightsizing recommendation on the computing capacity based on the computing utilization metrics and generating a memory capacity rightsizing recommendation on the memory capacity based on the memory utilization metrics. The method may further include determining a recommended instance type for the service resource unit based on the computing capacity rightsizing recommendation and the memory capacity rightsizing recommendation. The method may further include performing a storage volume check on the service resource unit to obtain a storage volume check result.

Abstract: A device may receive user personalized data and user activity data identifying tasks and actions performed by a user, and may perform natural language processing on the user personalized data and the user activity data to generate processed textual data. The device may train machine learning models based on the processed textual data to generate trained machine learning models, and may receive, from a client device, a command identifying a particular task to be performed. The device may process the command and the user activity data, with the trained machine learning models, to determine whether a particular action in the user activity data correlates with the particular task. The device may perform actions when the particular action correlates with the particular task.

Abstract: A multi-layer database sizing stack may generate prescriptive tier requisition tokens for controlling requisition of database-compute resources at database-compute tiers. The input layer of the database sizing stack may obtain historical data. The threading layer may be used to flag occurrences of single threading application execution. The change layer may be used to determine potential for a step based on compute utilization type data and assert flags indicating the potential. The step layer may determine if potential steps may be taken based on operation-rate type data and flush type data. The requisition layer may generate a tier requisition token based on the provisional requisition tokens generated at other layers and/or finalization directives obtained at the requisition layer.