Abstract: An embodiment for dynamic categorization of information technology (IT) service tickets is provided. The embodiment may include logging an IT service ticket when text is entered into a description field. The embodiment may also include creating a filtered description field by processing the text entered into the description field. The embodiment may further include computing a set of exponential weights and assigning the set of exponential weights to each word in the filtered description field. The embodiment may also include multiplying the set of exponential weights by the word's TF-IDF score to determine an IT service ticket category for placement of the IT service ticket into the IT service ticket category. The embodiment may further include generating features for machine learning, utilizing the generated features to build a supervised machine learning model, and evaluating the supervised machine learning model through analyzation of data from historical IT service tickets.

Abstract: This disclosure provides systems, devices, apparatus, and methods, including computer programs encoded on storage media, for synchronized dual eye variable refresh rate update for a VR display. A display processor obtains an indication of a synchronous flush or an asynchronous flush with respect to a first DPU and/or a second DPU. The display processor determines whether a first flush operation and/or a second flush operation is available at a time instance, where the first flush operation and the second flush operation are associated with the first DPU and/or the second DPU. The display processor performs, based on a VSync instance, the first flush operation and/or the second flush operation based on whether the first flush operation and/or the second flush operation are available at the time instance and based on the indication of the synchronous flush or the asynchronous flush.

Abstract: Analyzing log data, such as security log data and machine data, is disclosed. A baseline is built for a set of machine data. The baseline is built at least in part by determining a plurality of signature profiles for a plurality of respective time slices. An occurrence of an anomaly associated with the source of the machine data is determined. The occurrence is determined at least in part by determining that received machine data does not conform to the baseline within a threshold.

Abstract: Data migration based on data change rate analysis is provided. A minimum data replication duration is calculated for each respective data migration event of a set of data migration events in an existing data migration wave plan by adjusting a planned data replication duration until a data change rate per day of servers is equal to an estimated server data replication rate per day when the existing data migration wave plan is not feasible. A new data replication start date, a new data replication end date, and a new data migration cutover date is determined for each respective data migration event based on the minimum data replication duration for each respective data migration event. A new data migration wave plan is generated based on the new data replication start date, the new data replication end date, and the new data migration cutover date for each respective data migration event.

Abstract: The present invention relates to preservation of meat products. In particular new additives are provided for effective inhibition or prevention of bacterial outgrowth in meat products. The present inventors found that a combination of carvacrol and a cationic surfactant was effective in the inhibition or prevention of bacterial outgrowth in meat products. The combinations, more in particular, proved to be effective at levels that do not result in significant effects on the flavor and/or taste of the products. The present inventors furthermore found that treatment of meat products with the combinations of this invention had a favorable effect on the visual appearance (color) of the meat products. The present invention provides preservative compositions, the use of thereof as well as the meat products containing them.

Abstract: A method, system, and computer program product for open flow connection between differing software-defined network controllers are provided. The method generates a networking interface between a first networking controller and a second networking controller. Networking information is exchanged between the first networking controller and the second networking controller using the networking interface. A logical switch is generated between the first networking controller and the second networking controller by matching at least a portion of the networking information of the second networking controller at the first networking controller. The method exchanges the matched portion of the networking information from the first networking controller with the second networking controller to create layer two open flow connection between the first networking controller and the second networking controller.

Abstract: A method, system, and computer program product for open flow connection between differing software-defined network controllers are provided. The method generates a networking interface between a first networking controller and a second networking controller. Networking information is exchanged between the first networking controller and the second networking controller using the networking interface. A logical switch is generated between the first networking controller and the second networking controller by matching at least a portion of the networking information of the second networking controller at the first networking controller. The method exchanges the matched portion of the networking information from the first networking controller with the second networking controller to create layer two open flow connection between the first networking controller and the second networking controller.

Abstract: Automatic partitioning is disclosed. A set of previously run queries is obtained. The set of previously run queries is analyzed to determine one or more query fragments from the set of previously run queries. One or more partitions are generated at least in part by using the obtained query fragments.

Abstract: Computer-implemented methods, systems and computer program products leveraging blockchain networks to securely store a tamper-proof ledger comprising an audit trail describing the completion or missed data migration tasks, based on a timeline of an end-to-end data migration task schedule. Each of the event logs and alerts from the data migration source, data migration target, and/or migration tools, including network device logs, operating system logs, user-access logs, alerts, migration tool output etc. associated with the end-to-end migration tasks is made a part of the audit trail and stored to the ledger of the blockchain. All event logs, alert or other digital assets recorded to blocks of the blockchain can be timestamped, hashed and distributed across all nodes of the blockchain network and verified as valid by each of the peer nodes. As blocks updating the audit trail are added to the blockchain, the entries cannot be modified or tampered with.

Abstract: This disclosure relates generally to selection of cloud service providers in a multi-cloud. The selection of cloud service providers (CSPs) in a multi-cloud environment is challenging as it depends on multiple criteria such as security, usability, latency, and service cost. In an embodiment, for each CSP and multi-CSP combination, two decision problems are solved; namely, a VM selection problem and a cloud region selection problem, taking latency requirement and DR laws constraints into consideration. By solving the VM selection and CC selection problems, the service cost and the user to cloud region mapping are estimated. Using said estimates and other qualitative criteria, a multi-cloud multi-criteria decision problem is solved using MCDM techniques to rank the CSP combinations for each application. Based on the ranks and a constraint on a service cost of the entity one of a CSP and a CSP combination is selected for each application.

Abstract: Data migration based on data change rate analysis is provided. A minimum data replication duration is calculated for each respective data migration event of a set of data migration events in an existing data migration wave plan by adjusting a planned data replication duration until a data change rate per day of servers is equal to an estimated server data replication rate per day when the existing data migration wave plan is not feasible. A new data replication start date, a new data replication end date, and a new data migration cutover date is determined for each respective data migration event based on the minimum data replication duration for each respective data migration event. A new data migration wave plan is generated based on the new data replication start date, the new data replication end date, and the new data migration cutover date for each respective data migration event.

Abstract: Automatic partitioning is disclosed. A set of previously run queries is obtained. The set of previously run queries is analyzed to determine one or more query fragments from the set of previously run queries. One or more partitions are generated at least in part by using the obtained query fragments.

Abstract: Analyzing log data, such as security log data and machine data, is disclosed. A baseline is built for a set of machine data. The baseline is built at least in part by determining a plurality of signature profiles for a plurality of respective time slices. An occurrence of an anomaly associated with the source of the machine data is determined. The occurrence is determined at least in part by determining that received machine data does not conform to the baseline within a threshold.

Abstract: Analyzing log data, such as security log data and machine data, is disclosed. A baseline is built for a set of machine data. The baseline is built at least in part by determining a plurality of signature profiles for a plurality of respective time slices. An occurrence of an anomaly associated with the source of the machine data is determined. The occurrence is determined at least in part by determining that received machine data does not conform to the baseline within a threshold.

Abstract: Computer-implemented methods, systems and computer program products leveraging blockchain networks to securely store a tamper-proof ledger comprising an audit trail describing the completion or missed data migration tasks, based on a timeline of an end-to-end data migration task schedule. Each of the event logs and alerts from the data migration source, data migration target, and/or migration tools, including network device logs, operating system logs, user-access logs, alerts, migration tool output etc. associated with the end-to-end migration tasks is made a part of the audit trail and stored to the ledger of the blockchain. All event logs, alert or other digital assets recorded to blocks of the blockchain can be timestamped, hashed and distributed across all nodes of the blockchain network and verified as valid by each of the peer nodes. As blocks updating the audit trail are added to the blockchain, the entries cannot be modified or tampered with.

Abstract: An embodiment for dynamic categorization of information technology (IT) service tickets is provided. The embodiment may include logging an IT service ticket when text is entered into a description field. The embodiment may also include creating a filtered description field by processing the text entered into the description field. The embodiment may further include computing a set of exponential weights and assigning the set of exponential weights to each word in the filtered description field. The embodiment may also include multiplying the set of exponential weights by the word's TF-IDF score to determine an IT service ticket category for placement of the IT service ticket into the IT service ticket category. The embodiment may further include generating features for machine learning, utilizing the generated features to build a supervised machine learning model, and evaluating the supervised machine learning model through analyzation of data from historical IT service tickets.

Abstract: Single-click delta analysis is disclosed. A user query of status information collected from one or more monitored devices is received from a user. In response to receiving an indication from the user to determine a variance between different portions of the collected status information, a target query and a baseline query are generated using the user query. The generated target query and the generated baseline query are performed, respectively, against data in a data store including the status information collected from the one or more monitored devices. A target set of status information results and a baseline set of status information results are obtained in response to performing, respectively, the generated target query and the generated baseline query. The obtained target and baseline sets of results are combined. Output indicative of a variance between the target and baseline sets of status information results is provided based at least in part on the combining.

Abstract: Single-click delta analysis is disclosed. A user query of status information collected from one or more monitored devices is received from a user. In response to receiving an indication from the user to determine a variance between different portions of the collected status information, a target query and a baseline query are generated using the user query. The generated target query and the generated baseline query are performed, respectively, against data in a data store including the status information collected from the one or more monitored devices. A target set of status information results and a baseline set of status information results are obtained in response to performing, respectively, the generated target query and the generated baseline query. The obtained target and baseline sets of results are combined. Output indicative of a variance between the target and baseline sets of status information results is provided based at least in part on the combining.

Abstract: Data is an asset to any organization and any breach to the data during task allocation to agents may lead to serious damage to organizations including loss of consumer confidence, trust, reputation, financial penalties and the like. Conventional methods mainly focus on the allocating task to agents based on user satisfaction, overall throughput and maximize revenue and less focus is given to data privacy. The present subject matter overcomes the limitations of the conventional methods for task allocation by utilizing a dynamic data exposure analysis method, which enables seamless upgrading of the data access policy and or control. Here, a data exposure is monitored based on a data exposure score, dynamic identification of conflicting tasks and a dynamic privacy budget. The data exposure score is calculated in two execution points. Finally all the values are updated in the system for utilization in the further privacy enabled task allocation.

Abstract: This disclosure relates generally to selection of cloud service providers in a multi-cloud. The selection of cloud service providers (CSPs) in a multi-cloud environment is challenging as it depends on multiple criteria such as security, usability, latency, and service cost. In an embodiment, for each CSP and multi-CSP combination, two decision problems are solved; namely, a VM selection problem and a cloud region selection problem, taking latency requirement and DR laws constraints into consideration. By solving the VM selection and CC selection problems, the service cost and the user to cloud region mapping are estimated. Using said estimates and other qualitative criteria, a multi-cloud multi-criteria decision problem is solved using MCDM techniques to rank the CSP combinations for each application. Based on the ranks and a constraint on a service cost of the entity one of a CSP and a CSP combination is selected for each application.