Abstract: A computer-implemented method includes: monitoring, by a user device, a location of the user device; determining, by the user device and based on the monitoring, that the user is within a threshold distance or a threshold arrival time of the service provider location; and outputting, by the user device, user information to the service provider based on the determining that the user is within the threshold distance or the threshold arrival time of the service provider location. The user information indicates services to provide to the user by the service provider upon the user's arrival to the service provider location. The outputting causes the service provider to receive the user information for serving the user upon the user's arrival to the service provider location.

Abstract: A method, system and computer product for performing storage maintenance is described. A training set for storage volume reclamation is received. The training set for storage volume reclamation contains sets of storage parameters for storage volumes and corresponding user decisions whether the storage volumes are reclaimable. The training set is used to train a machine learning system to recognize reclaimable candidate storage volumes. The trained machine learning system is used to determine that a candidate storage volume for reclamation is likely a reclaimable storage volume.

Abstract: Systems and methods for computer-based escalation detection are disclosed. In embodiments, a method includes: determining an occurrence of an interaction event between a first party and a second party within a recording including audio data; analyzing the audio data; determining, based on the analyzing the audio data, an escalation during the interaction event to generate escalation data; saving the escalation data; partitioning each interaction event into a plurality of sections, wherein a first section represents a start of the interaction event, and another section represents an end of the interaction event; assigning a sentiment score for each of the plurality of sections; and calculating an overall sentiment score for the interaction event by combining the sentiment scores for each of the plurality of sections, wherein the saved escalation data includes the overall sentiment score.

Abstract: A method, executed by one or more processors, includes identifying at least one product for delivery and create a shipping manifest for the at least one product. The method includes extracting from the shipping manifest, a required amount of storage space for the at least one product and one or more environmental conditions required for storage of the at least one product at the receiving location. Furthermore, the method includes identifying a storage space location for storage of the at least one product at the receiving location, wherein the identified storage space location provides the required amount of storage space and the one or more environmental conditions required for the at least one product.

Abstract: A computer-implemented method includes: monitoring, by a user device, a location of the user device; determining, by the user device and based on the monitoring, that the user is within a threshold distance or a threshold arrival time of the service provider location; and outputting, by the user device, user information to the service provider based on the determining that the user is within the threshold distance or the threshold arrival time of the service provider location. The user information indicates services to provide to the user by the service provider upon the user's arrival to the service provider location. The outputting causes the service provider to receive the user information for serving the user upon the user's arrival to the service provider location.

Abstract: A method, system and computer product for performing storage maintenance is described. A training set for storage volume reclamation is received. The training set includes a set of storage parameters, each set of storage parameters corresponds to a respective candidate storage volume of a set of candidate storage volumes. The training set also includes a set of user decisions made whether a respective candidate storage volume is reclaimable. The training set is used to train a machine learning system to recognize common features of reclaimable candidate storage volumes. A set of candidate storage volumes is provided for potential reclamation, each with a set of storage parameters. A graphical user interface presents respective members of the set of candidate storage volumes for reclamation if a confidence level is calculated that the respective candidate storage volume is reclaimable exceeds a threshold.

Abstract: A method, system and computer product for performing storage maintenance is described. A training set for storage volume reclamation is received. The training set for storage volume reclamation contains sets of storage parameters for storage volumes and corresponding user decisions whether the storage volumes are reclaimable. The training set is used to train a machine learning system to recognize reclaimable candidate storage volumes. The trained machine learning system is used to determine that a candidate storage volume for reclamation is likely a reclaimable storage volume.

Abstract: A computer-implemented method includes: monitoring, by a user device, a location of the user device; determining, by the user device and based on the monitoring, that the user is within a threshold distance or a threshold arrival time of the service provider location; and outputting, by the user device, user information to the service provider based on the determining that the user is within the threshold distance or the threshold arrival time of the service provider location. The user information indicates services to provide to the user by the service provider upon the user's arrival to the service provider location. The outputting causes the service provider to receive the user information for serving the user upon the user's arrival to the service provider location.

Abstract: At an application executing in a system, a usage pattern of the system and an entry in a data use history of the system are analyzed. Responsive to the analyzing, a data item is identified for caching at the system, wherein the data item is accessible to the system from at a remote data processing system over a data network at a present time, and the data item will be requested from the system at a future time when no network connectivity will be available to the system. A determination is made whether a caching control prevents the caching of the data item at the system. Responsive to the caching control not preventing the caching of the data item, the data item is cached on the system.

Abstract: Systems and methods for computer-based escalation detection are disclosed. In embodiments, a method includes: determining an occurrence of an interaction event between a first party and a second party within a recording including audio data; analyzing the audio data; determining, based on the analyzing the audio data, an escalation during the interaction event to generate escalation data; saving the escalation data; partitioning each interaction event into a plurality of sections, wherein a first section represents a start of the interaction event, and another section represents an end of the interaction event; assigning a sentiment score for each of the plurality of sections; and calculating an overall sentiment score for the interaction event by combining the sentiment scores for each of the plurality of sections, wherein the saved escalation data includes the overall sentiment score.

Abstract: Systems an methods of computer-based escalation detection are disclosed. In embodiments, a method includes: determining an occurrence of an interaction event between a first and second party within a recording including audio data; analyzing the audio data; determining an escalation during the interaction event to generate escalation data; partitioning each interaction event into a plurality of sections; assigning a sentiment score for each of the plurality of section; calculating an overall sentiment score for the interaction event, wherein the saved escalation data includes the overall sentiment score; graphing the overall sentiment score for the interaction event with a plurality of additional overall sentiment scores from respective additional interaction events to produce a graph of sentiment scores over time; and detecting a pattern of increasing of decreasing overall sentiment scores over time based on the graph.

Abstract: For analytic-based control of energy consumption, an appliance module receives an appliance identifier of an appliance connected to a power outlet, a selection module selects a power model for the power outlet based on the appliance identifier, the power model designating times that the power outlet is to be powered and times that the power outlet is to be unpowered, a usage module receives energy usage data for a power outlet, a presence module receives user presence data for a locale containing the power outlet, a update module modifies a power model for the power outlet based on the energy usage data and the user presence data, and a power control module selectively provides electrical power to the power outlet according to the power schedule.

Abstract: At an application executing in a system, a usage pattern of the system and an entry in a data use history of the system are analyzed. Responsive to the analyzing, a data item is identified for caching at the system, wherein the data item is accessible to the system from at a remote data processing system over a data network at a present time, and the data item will be requested from the system at a future time when no network connectivity will be available to the system. A determination is made whether a caching control prevents the caching of the data item at the system. Responsive to the caching control not preventing the caching of the data item, the data item is cached on the system.

Abstract: A method for managing a rechargeable battery. The method includes a computer processor identifying a rechargeable battery within a first device. The method further includes a computer processor identifying a battery maintenance policy associated with the rechargeable battery. The method further includes a computer processor determining a first set of models for implementing the identified battery maintenance policy on the identified rechargeable battery based on the identified battery maintenance policy and one or more environmental factors corresponding to the first device. The method further includes a computer processor installing the first set of models in the first device. The method further includes a computer processor performing an intervention action based, at least in part, on a current state of the first set of models and one or more current environmental factors corresponding to the first device.

Abstract: Systems and methods for securing an emergency exit door on an armrest of a seat are provided. A system includes a latch connected to an armrest of a seat of a vehicle. The latch is moveable relative to the armrest between a stowed position and a deployed position. The latch is structured and arranged to engage an edge of a door that is associated with an exit of the vehicle to hold the door on the armrest.

Abstract: A method for managing a rechargeable battery. The method includes a computer processor identifying a rechargeable battery within a first device. The method further includes a computer processor identifying a battery maintenance policy associated with the rechargeable battery. The method further includes a computer processor determining a first set of models for implementing the identified battery maintenance policy on the identified rechargeable battery based on the identified battery maintenance policy and one or more environmental factors corresponding to the first device. The method further includes a computer processor installing the first set of models in the first device. The method further includes a computer processor performing an intervention action based, at least in part, on a current state of the first set of models and one or more current environmental factors corresponding to the first device.

Abstract: A method for managing a rechargeable battery. The method includes a computer processor identifying a rechargeable battery within a first device. The method further includes a computer processor identifying a battery maintenance policy associated with the rechargeable battery. The method further includes a computer processor determining a first set of models for implementing the identified battery maintenance policy on the identified rechargeable battery based on the identified battery maintenance policy and one or more environmental factors corresponding to the first device. The method further includes a computer processor installing the first set of models in the first device. The method further includes a computer processor performing an intervention action based, at least in part, on a current state of the first set of models and one or more current environmental factors corresponding to the first device.

Abstract: A method for automatically prioritizing startup of resource groups during a migration event. The method may include monitoring resource usage of a first and a second set of applications associated, respectively, with a first and a second resource group executing on a first computing node. The method may additionally include generating respective first and second resource usage models for the first and second resource groups based on resource usage. The method may then include extrapolating, based on the first and second resource usage models, respective first and second resource group usage scores for the first and second resource groups at a second time in response to a migration event, the second time occurring subsequent to the first time. The method may further include determining, based on the extrapolating, a priority order for serially starting the first and second set of applications on a second computing node at the second time.

Abstract: At an application executing in a system, a usage pattern of the system and an entry in a data use history of the system are analyzed. Responsive to the analyzing, a data item is identified for caching at the system, wherein the data item is accessible to the system from at a remote data processing system over a data network at a present time, and the data item will be requested from the system at a future time when no network connectivity will be available to the system. A determination is made whether a caching control prevents the caching of the data item at the system. Responsive to the caching control not preventing the caching of the data item, the data item is cached on the system.

Abstract: Systems and methods for escalation detection using sentiment analysis are disclosed. A computer-implemented method of the invention includes: determining, by a computer device, the occurrence of an interaction event between a first party and a second party within a recording including audio data; analyzing, by the computer device, the audio data for a change in tone over time; analyzing, by the computer device, the audio data for the presence of any negative tones; determining, by the computer device, whether the change in tone, the presence of any negative tones, or a combination of the change in tone and the presence of any negative tones, indicates an escalation during the interaction event to generate escalation data; and saving, by the computer device, the escalation data.