Abstract: The invention pertains to a multi-step process for making polyfunctional aromatic compounds comprising two phenyl rings bearing reactive groups susceptible of polycondensation reaction to provide polycondensed polymers, said method using economic raw materials, and possessing high selectivity and overall yield.

Abstract: At least some embodiments are directed to a system that receives from an online portal loaded in a computing device, a user request to instantiate a server cluster in a hybrid computer network. The system authenticates and redirects the user request to a selected computer network configured in the hybrid computer network. The system instantiates the server cluster in the selected computer network causing the server cluster to initiate a microservice agent during bootup. The system sends a command to the server cluster to initiate the execution of a process and receives from the microservice agent event data associated with the process. The system inputs the event data into a trained machine learning model to determine a first execution state of the process and sends a command to change the first execution state of the process to a second execution state.

Abstract: At least some embodiments are directed to an insights inference system that produces multiple insights associated with an entity. The insights inference system generates a decision tree machine learning model, assigning a first insight to a parent node of a decision tree machine learning model and assigning at least one second insight to child nodes of the decision tree machine learning model. Each child node is associated with a sequence number and a rank number. The sequence number and the rank number are indicative of a significance associated with the at least one second insight. The insight inference system responds to queries by traversing the decision tree machine learning model to compute at least one response insight based on the sequence number and the rank number associated with each child node and outputs the at least one response insight to a client terminal.

Abstract: Disclosed are various embodiments for extracting transaction and user data from financial documents and formatting the data into a structured format to facilitate a real-time analysis of the extracted data. A user may submit an unstructured formatted financial document with a credit rating request, underwriting request, and/or other type of financial risk assessment request. Text components and a table component are identified according to a structural representation of the document. The text components are analyzed to identify and extract ownership data associated with the user that can be used to verify ownership of the provided document by the submitting user. The transaction data is identified and extracted in a structured format based at least in part on a table header location and detected column boundaries. The extracted transaction data is validated to ensure an accurate extraction of the transaction data.

Abstract: Embodiments of the present disclosure disclose methods and systems for generating operational alarms for a plurality of clients, the operational alarms being generated by a business performance system, each client being associated with a plurality of Key Performance Indicators (KPIs). An aggregate rank for each client based on ranks of each KPI is generated. For each client: the aggregate rank of the client over one or more time periods is monitored. If the aggregate rank deteriorates over the one or more time periods, a severity indicator is determined based on change of value of each KPI and change of rank of each KPI for the client over the one or more time periods. An operational alarm based on value of the severity indicator is determined. The operational alarm is displayed on a user interface, wherein the operational alarm displays one or more KPIs with highest severity values.

Abstract: At least some embodiments are directed to a system that receives from an online portal loaded in a computing device, a user request to instantiate a server cluster in a hybrid computer network. The system authenticates and redirects the user request via a proxy service to a selected computer network configured in the hybrid computer network. The system instantiates the server cluster in the selected computer network causing the server cluster to initiate a microservice agent during bootup. The system sends a command to the server cluster to initiate the execution of a process and receives from the microservice agent event data associated with the process. The system inputs the event data into a trained machine learning model to determine a first execution state of the process and sends a command to change the first execution state of the process to a second execution state.

Abstract: A technique for caching evidence for answering questions in a cache memory of a data processing system (that is configured to answer questions) includes receiving a first question. The first question is analyzed to identify a first set of characteristics of the first question. A first set of evidence for answering the first question is loaded into the cache memory. A second question is received. The second question is analyzed to identify a second set of characteristics of the second question. A portion of the first set of evidence, whose expected usage in answering the second question is below a determined threshold, is unloaded from the cache memory.

Abstract: A technique for caching evidence for answering questions in a cache memory of a data processing system (that is configured to answer questions) includes receiving a first question. The first question is analyzed to identify a first set of characteristics of the first question. A first set of evidence for answering the first question is loaded into the cache memory. A second question is received. The second question is analyzed to identify a second set of characteristics of the second question. A portion of the first set of evidence, whose expected usage in answering the second question is below a determined threshold, is unloaded from the cache memory.

Abstract: A method, system and computer program product for selecting virtual machines to be migrated to a public cloud. The current resource usage for virtual machine instances running in the private cloud is determined. Furthermore, any scaling policies attached to the virtual machine instances running in the private cloud are obtained. Additional resource usages for any of the virtual machine instances with a scaling policy are computed for when these virtual machine instances are scaled out. A cost of running a virtual machine instance in the public cloud is then determined using its current resource usage as well as any additional resource usage if a scaling policy is attached to the virtual machine instance based on the cost for running virtual machine instances in a public cloud. If the cost is less than a threshold cost, then the virtual machine instance is selected to be migrated to the public cloud.

Abstract: A computer-implemented method for deploying a plurality of data conversion flow between a first application in a first system to a second application in a second system, without restarting the plurality of data conversation flow, is provided. The computer-implemented method may further include providing a plurality of modifiable data conversation that identifies a plurality of input parameters, a plurality of data formats, a plurality of data description, a plurality of conversation routines, a plurality of paths of the conversion routines, and a plurality of output information that determines routes of converted data for the first application. The computer-implemented method may further include converting the plurality of modifiable data conversion to form a data input from the first application to the second application.

Abstract: A management system receives inputs over a period of time from outputs of one or more sensors placed within a proximity to a service area, the one or more sensors for detecting at least one of at least one weight and at least one sound. The management system dynamically estimating, based on a rate of a percentage of change of the at least one weight over the period of time and types of sounds of the at least one sound for the service area, one or more wait times until a completion of use of the service area. The management system dynamically generating one or more wait time estimates in real time for the service area based on the one or more wait times and a current number of users waiting in a queue for the service area.

Abstract: According to one aspect of the present disclosure a method and technique for dynamic system level agreement provisioning is disclosed. The method includes: identifying, by a data processing system of a computing environment service provider, service level criteria for a customer of computing services; determining characteristics of the computing environment; identifying a time period for providing the computing services; evaluating one or more utility functions defining service level variables; and automatically determining, by the data processing system, a service level agreement (SLA) provision for the customer based on the one or more utility functions.

Abstract: According to one aspect of the present disclosure a system and technique for dynamic system level agreement provisioning includes: a computing environment configured with allocatable computing resources; and a host having a processor unit operable to execute a service level agreement (SLA) module. The SLA module is configured to: identify service level criteria for a customer of computing services of the computing environment; determine characteristics of the computing environment; identify a time period for providing the computing services; evaluate one or more utility functions defining service level variables; and automatically determine a service level agreement (SLA) provision for the customer based on the one or more utility functions.

Abstract: In some aspects, a computer-implemented method for diagnosing an unfavorable mobile application user experience is described. The method may include retrieving user application interaction data from a mobile device, inter-correlating the user application interaction data, updating a user interaction database with the inter-correlated user application data, and diagnosing, via a processor operatively connected to the user interaction database, information indicative of a cause of the unfavorable user experience.

Abstract: A method is provided for building patterns with high level pattern topology requirements for deployment across multiple systems. The patterns are built based on pattern capabilities and configurations of the multiple systems. Such patterns can meet the desired pattern capabilities including high availability and/or continuous capabilities.

Abstract: A method, system and computer program product for selecting virtual machines to be migrated to a public cloud. The current resource usage for virtual machine instances running in the private cloud is determined. Furthermore, any scaling policies attached to the virtual machine instances running in the private cloud are obtained. Additional resource usages for any of the virtual machine instances with a scaling policy are computed for when these virtual machine instances are scaled out. A cost of running a virtual machine instance in the public cloud is then determined using its current resource usage as well as any additional resource usage if a scaling policy is attached to the virtual machine instance based on the cost for running virtual machine instances in a public cloud. If the cost is less than a threshold cost, then the virtual machine instance is selected to be migrated to the public cloud.

Abstract: In one aspect, a computer-implemented method for compressing content based on a social factor, an environmental factor, and a relational factor is described. The method may include monitoring access to the content, forming, by a processor, a contextual evaluation based on the monitored access and determining an importance of the content based on the contextual evaluation. The method may further include storing the content in a compressed form, where the compressed form is selected based on the importance.

Abstract: A computer-implemented method for deploying a plurality of data conversion flow between a first application in a first system to a second application in a second system, without restarting the plurality of data conversation flow, is provided. The computer-implemented method may further include providing a plurality of modifiable data conversation that identifies a plurality of input parameters, a plurality of data formats, a plurality of data description, a plurality of conversation routines, a plurality of paths of the conversion routines, and a plurality of output information that determines routes of converted data for the first application. The computer-implemented method may further include converting the plurality of modifiable data conversion to form a data input from the first application to the second application.

Abstract: A method, system and computer program product for selecting virtual machines to be migrated to a public cloud. The current resource usage for virtual machine instances running in the private cloud is determined. Furthermore, any scaling policies attached to the virtual machine instances running in the private cloud are obtained. Additional resource usages for any of the virtual machine instances with a scaling policy are computed for when these virtual machine instances are scaled out. A cost of running a virtual machine instance in the public cloud is then determined using its current resource usage as well as any additional resource usage if a scaling policy is attached to the virtual machine instance based on the cost for running virtual machine instances in a public cloud. If the cost is less than a threshold cost, then the virtual machine instance is selected to be migrated to the public cloud.

Abstract: A method, system and computer program product for selecting virtual machines to be migrated to a public cloud. The current resource usage for virtual machine instances running in the private cloud is determined. Furthermore, any scaling policies attached to the virtual machine instances running in the private cloud are obtained. Additional resource usages for any of the virtual machine instances with a scaling policy are computed for when these virtual machine instances are scaled out. A cost of running a virtual machine instance in the public cloud is then determined using its current resource usage as well as any additional resource usage if a scaling policy is attached to the virtual machine instance based on the cost for running virtual machine instances in a public cloud. If the cost is less than a threshold cost, then the virtual machine instance is selected to be migrated to the public cloud.