Abstract: The present invention relates generally to a trimming guide to enable a person with or without particular skill, or a robot, or a computer, or a numerical device to cut a predetermined design, style or shape. More particularly, the invention relates to a trimming guide that would enable a person by him or herself, with or without training or particular skill, or through the use of a robot or a computer or a numerical device to trim his or her own hair, or another person's hair to a quality, finished state which is a predetermined design, style or shape.

Abstract: A computer-implemented method for determining whether an electric vehicle (EV) requires a current charge. The method analyzes a set of EV data, wherein the set of EV data comprises a battery level, a destination, a current position, and a predicted arrival time to the destination. The method further constructs a charging regulation model for the EV, based on the analyzed set of EV data. The method further computes a risk score pertaining to charging the EV, based on the constructed charging regulation model for the EV, and determines whether the EV requires a current charge based on the computed risk score. The method further engages one or more wireless charging points on a roadway, if the computed risk score is below a threshold value.

Abstract: The present invention relates generally to a trimming guide to enable a person with or without particular skill, or a robot, or a computer, or a numerical device to cut a predetermined design, style or shape. More particularly, the invention relates to a trimming guide that would enable a person by him or herself, with or without training or particular skill, or through the use of a robot or a computer or a numerical device to trim his or her own hair, or another person’s hair to a quality, finished state which is a predetermined design, style or shape.

Abstract: A computer-implemented method includes observing, by a computer device, a plurality of uniform resource locators (URLs); parsing, by the computer device, a URL path of each of the URLs into path segments; creating, by the computer device, a tree structure, the tree structure having a plurality of nodes, each node representing a particular path segment of the path segments; determining, by the computer device, a confidence factor for a first path in the tree structure using a decay function, the first path having an end node; and compacting, by the computer device, sibling nodes of the nodes into a compacted node in response to a number of the sibling nodes exceeding a variance threshold.

Abstract: In an approach for optimally grouping containers, a processor passively monitors a set of parameters for a set of containers within a network. A processor records the set of parameters for each container of the set of containers. A processor deploys a k-nearest neighbor neural network (KNN) to determine a first set of groupings of the set of containers based on the set of parameters. A processor simulates the network having grouped containers based on the first set of groupings of the set of containers output by the KNN. A processor simulates an action on the set of containers. A processor updates a reward function based on the action. A processor determines whether a maximum value of the reward function is reached.

Abstract: Embodiments of the present invention provide methods, computer program products, and systems. Embodiments of the present invention can be used to partition an area into zones, wherein each zone includes one or more delivery mechanisms and each delivery mechanism include one or more portions that are capable of charging an electric vehicle. Embodiments of the present invention can be used to, in response to receiving a request to charge, reserve a portion of a delivery mechanism for a fixed period of time based on available capacity of the delivery mechanism and need of the requesting electric vehicle. Embodiments of the present invention can be further used to modify the fixed period of time based on real time use of the delivery mechanism.

Abstract: A computer-implemented method for prioritizing one or more electric vehicles that need a battery charge while driving. The method receives a wireless communication between one or more electric vehicles on a section of the roadway. The method further communicates a risk score between the one or more electric vehicles, based on a charging regulation model. The method further prioritizes a need for a battery charge, for the one or more electric vehicles on the section of the roadway, based on the communicated risk score. The method further engages one or more wireless charging points on the section of the roadway, with the one or more electric vehicles, based on the prioritized need for a battery charge.

Abstract: A computer-implemented method to determine which port in a container is a service port. The method includes identifying, a first container, wherein the first container comprises a plurality of ports. The method further includes, training a neural network, wherein the neural network is configured to identify at least one service port from the plurality of ports. The method further includes, monitoring, by a network monitor, a set of data sent to the first container comprising a first parameter. The method includes, identifying a first service port of the plurality of ports. The method further includes, marking the first service port.

Abstract: Embodiments of the present invention provide a computer system, a computer program product, and a method that comprises identifying a first user of a plurality of users; identifying a location for the first user; transmitting input of the first user to a server computing device; and simultaneously displaying multiple personalized, dynamic displays using diffraction grating based off of input of the first user and location of the first user.

Abstract: Methods, systems and computer program products are described herein that provided context to user queries to a chat bot. In one embodiment, the method may include receiving a user query at a chat bot. The chat bot is communicating with a system providing conversation interaction with the user. The chat bot accessing a user profile being initiated by the user. The user can revoke the permission to the system for creating and/or using a user profile at any time. In some embodiments, the user profile includes a query history and profile information about the user that correlates keywords to context. The chat bot weighs query keywords for comparison with the keywords of the user profile that are correlated to context. The chat bot interacts with the user using the context correlated to the user in accordance with the weight of the query keywords matched to the keywords of the user profile that are correlated to the context.

Abstract: A computer-implemented method to determine which port in a container is a service port. The method includes identifying, a first container, wherein the first container comprises a plurality of ports. The method further includes, training a neural network, wherein the neural network is configured to identify at least one service port from the plurality of ports. The method further includes, monitoring, by a network monitor, a set of data sent to the first container comprising a first parameter. The method includes, identifying a first service port of the plurality of ports. The method further includes, marking the first service port.

Abstract: Embodiments of the present invention provide methods, computer program products, and systems. Embodiments of the present invention can be used to partition an area into zones, wherein each zone includes one or more delivery mechanisms and each delivery mechanism include one or more portions that are capable of charging an electric vehicle. Embodiments of the present invention can be used to, in response to receiving a request to charge, reserve a portion of a delivery mechanism for a fixed period of time based on available capacity of the delivery mechanism and need of the requesting electric vehicle.

Abstract: A computer-implemented method for prioritizing one or more electric vehicles that need a battery charge while driving. The method receives a wireless communication between one or more electric vehicles on a section of the roadway. The method further communicates a risk score between the one or more electric vehicles, based on a charging regulation model. The method further prioritizes a need for a battery charge, for the one or more electric vehicles on the section of the roadway, based on the communicated risk score. The method further engages one or more wireless charging points on the section of the roadway, with the one or more electric vehicles, based on the prioritized need for a battery charge.

Abstract: A computer-implemented method for determining whether an electric vehicle (EV) requires a current charge. The method analyzes a set of EV data, wherein the set of EV data comprises a battery level, a destination, a current position, and a predicted arrival time to the destination. The method further constructs a charging regulation model for the EV, based on the analyzed set of EV data. The method further computes a risk score pertaining to charging the EV, based on the constructed charging regulation model for the EV, and determines whether the EV requires a current charge based on the computed risk score. The method further engages one or more wireless charging points on a roadway, if the computed risk score is below a threshold value.

Abstract: Mitigating threats to container-based workloads is provided by a process that includes detecting an attack against a container hosting environment that includes active and reserve container pools. The attack poses a potential threat of contamination to hosted containers. Based on detecting the attack, the process identifies a time-to-contamination, taken as an amount of time for an active container of the active container pool to become contaminated as a result of the attack. The process provisions new containers into the reserve container pool at a determined rate that is based on the identified time-to-contamination, and continuously removes, from the active container pool, active containers servicing the workload and concurrently deploys reserve containers from the reserve container pool to the active container pool to replace the removed active containers and takeover servicing the workload.

Abstract: Managing container applications by providing a registry of managed container base images, each managed container base image wrapped to include an injection point, determining that a managed container base image includes a vulnerability, and creating a patch script to address the vulnerability. Managing container applications further includes inserting the patch script at the injection point and issuing a pull command for an application using the managed container base image, to a container orchestration tool.

Abstract: A computer-implemented method includes observing, by a computer device, a plurality of uniform resource locators (URLs); parsing, by the computer device, a URL path of each of the URLs into path segments; creating, by the computer device, a tree structure, the tree structure having a plurality of nodes, each node representing a particular path segment of the path segments; determining, by the computer device, a confidence factor for a first path in the tree structure using a decay function, the first path having an end node; and compacting, by the computer device, sibling nodes of the nodes into a compacted node in response to a number of the sibling nodes exceeding a variance threshold.

Abstract: Embodiments of the present invention provide a computer system, a computer program product, and a method that comprises identifying a first user of a plurality of users; identifying a location for the first user; transmitting input of the first user to a server computing device; and simultaneously displaying multiple personalized, dynamic displays using diffraction grating based off of input of the first user and location of the first user.

Abstract: In an approach for optimally grouping containers, a processor passively monitors a set of parameters for a set of containers within a network. A processor records the set of parameters for each container of the set of containers. A processor deploys a k-nearest neighbor neural network (KNN) to determine a first set of groupings of the set of containers based on the set of parameters. A processor simulates the network having grouped containers based on the first set of groupings of the set of containers output by the KNN. A processor simulates an action on the set of containers. A processor updates a reward function based on the action. A processor determines whether a maximum value of the reward function is reached.

Abstract: Mitigating threats to container-based workloads is provided by a process that includes detecting an attack against a container hosting environment that includes active and reserve container pools. The attack poses a potential threat of contamination to hosted containers. Based on detecting the attack, the process identifies a time-to-contamination, taken as an amount of time for an active container of the active container pool to become contaminated as a result of the attack. The process provisions new containers into the reserve container pool at a determined rate that is based on the identified time-to-contamination, and continuously removes, from the active container pool, active containers servicing the workload and concurrently deploys reserve containers from the reserve container pool to the active container pool to replace the removed active containers and takeover servicing the workload.