Abstract: Sensor data can be collected from a first set of sensors associated with a first seat within a vehicle during a first vehicle stage. The outputs of each sensor of the first set of sensors can then be aggregated to calculate a probability of life within the first seat during the first vehicle stage.

Abstract: In an approach for selectively placing an advertisement in a media item to maximize user engagement, a processor analyzes the media item by performing a static and dynamic scan. A processor determines whether it is more likely the user will engage with an advertisement placed in a foreground section or a background section of the media item. Responsive to determining it is more likely the user engages with the advertisement placed in the foreground section of the media item, a processor loads a set of time intervals associated with the peak regions of the media item. Responsive to determining the level of engagement by the user with the potential advertisement exceeds the threshold when the potential advertisement is associated with the media item, a processor associates the advertisement with the media item. A processor dynamically changes a background music of the advertisement with a sound extracted from the media item.

Abstract: A method includes: creating and maintaining, by a cloud object storage server, plural order data structures that define respective orders of objects stored in a bucket in a cloud object storage system; receiving, from a client device, a request to download the objects using one of the respective orders; allocating an iterator for the request, wherein the iterator is associated with a respective one of the plural order data structures that defines the one of the respective orders; returning an iterator identifier of the iterator to the client device; receiving, from the client device, a call containing the iterator identifier; and returning the objects to the client device in the one of the respective orders using the iterator and the respective one of the plural order data structures.

Abstract: The method provides for detecting information associated with consumed food. Data associated with detection events of food for possible consumption by a user is received from a plurality of sources. The data of detected food is parsed using a first criteria and parsing of event metadata is done using a second criteria and the data received from the detection event. Aggregate data is created for the food items by combining the detected food item data and the respective metadata of the detection event. An ordered list of food items from the aggregate data is generated and arranged according to a determined user consumption probability for the ordered list food items. The aggregate data of respective food items of the ordered list includes nutritional information of macronutrients and calories, accessed from a database, and the list of food items potentially consumed by the user are formatted into a predetermined form.

Abstract: Embodiments herein disclose computer-implemented methods, computer program products and computer systems including one or more processors configured for receiving user profile data corresponding to a plurality of user profiles each comprising profile attributes, determining profile attribute match scores for each of the profile attributes between each of the plurality of user profiles based on respective profile attribute pairs, and generating mentorship match data based on the profile attribute match scores, wherein the mentorship match data corresponds to a mentorship match between each pair of the plurality of user profiles.

Abstract: A computer-implemented system and method operate an automatic and adaptive animal behavioral system. The system receives user configuration and feedback, and generates a training set based on online animal behavior patterns and received user feedback. The system trains one or multiple models based on the training set, if the training set is sufficiently large. It then validates the models, and provides system generated classifications and action types and levels for animal’s behavior patterns, if the models’ accuracy rate is above a threshold.

Abstract: A computer-implemented method, a computer program product, and a computer system for placements of workloads in a system of multiple platforms as a service. A computer detects a triggering event for modifying a matrix that pairs respective workloads on respective platforms and includes attributes of running respective workloads on respective platforms. The computer recalculates the attributes in the matrix, in response to the triggering event being detected. The computer determines optimal placements of the respective workloads on the respective platforms, based on information in the matrix. The computer places the respective workloads on the respective platforms, based on the optimal placements.

Abstract: Systems, computer-implemented methods, and computer program products to facilitate optimization of resource usage based on quota trees are provided. According to an embodiment, a system can comprise a processor that executes computer executable components stored in memory. The computer executable components comprise a determination component that determines one or more quota trees that classify a job request as inadmissible. The computer executable components further comprise an optimization component that optimizes resource usage to enable admissibility of the job request based on the one or more quota trees.

Abstract: Systems, computer-implemented methods, and computer program products to facilitate using multiple quota trees in resource scheduling are provided. According to an embodiment, a system can comprise a processor that executes computer executable components stored in memory. The computer executable components comprise an evaluation component that executes admissibility of a job request based on a scope property of one or more quota trees that apply to the job request.

Abstract: A computer-implemented method, a computer program product, and a computer system for optimizing workload placements in a system of multiple platforms as a service. A computer first places respective workloads on respective platforms that yield lowest costs for the respective workloads. The computer determines whether mandatory constraints are satisfied. The computer checks best effort constraints, in response to the mandatory constraints being satisfied. The computer determines a set of workloads for which the best effort constraints are not satisfied and determines a set of candidate platforms that yield the lowest costs and enable the best effort constraints to be satisfied. From the set of workloads, the computer selects a workload that has a lowest upgraded cost and updates the workload by setting an upgraded platform index.

Abstract: The method provides for detecting information associated with consumed food. Data associated with detection events of food for possible consumption by a user is received from a plurality of sources. The data of detected food is parsed using a first criteria and parsing of event metadata is done using a second criteria and the data received from the detection event. Aggregate data is created for the food items by combining the detected food item data and the respective metadata of the detection event. An ordered list of food items from the aggregate data is generated and arranged according to a determined user consumption probability for the ordered list food items. The aggregate data of respective food items of the ordered list includes nutritional information of macronutrients and calories, accessed from a database, and the list of food items potentially consumed by the user are formatted into a predetermined form.

Abstract: A set of incoming lanes are identified within a pre-determined proximity of a traffic signal as candidate lanes to receive a go-signal from the traffic signal. A prioritized overall lane wait time is calculated for each incoming lane. Selected lanes receive the go-signal in the current iteration, based on the prioritized overall lane wait time. An amount of time to allocate to the go-signal is calculated, based on the number of vehicles to flush from the selected lanes. The go-signal is presented to the selected lanes for the allocated time, including non-conflicting lanes. A set of metrics are collected including throughput of vehicles leaving the pre-determined proximity of the traffic signal. Based on the metrics, a time allocation is determined for the next iteration of the go-signal, parameters are updated for the prioritized overall lane wait time, and the next iteration of the traffic signal is initiated.

Abstract: A method, computer program product and computer system to calculate resource quotas in a distributed computing environment are provided. A processor retrieves workload data regarding a plurality of workloads in a shared computing environment, where the plurality of workloads are executing or pending execution within the shared computing environment. A processor identifies a plurality of tenants of the shared computing environment associated with the plurality of workloads. A processor determines an expected resource usage for the plurality of tenants. A processor determines a ratio of resource usage for the plurality of tenants. A processor determines a resource limit for the plurality of tenants. A processor adjusts at least one aspect of the shared computing environment based on a determination that a total expected resource usage for both executing and pending workloads of a tenant exceeds a resource limit associated with the tenant.

Abstract: A computer-implemented method for determining aggregate health risk factors comprising one or more processors configured for receiving individual profile data comprising individual attributes corresponding to an individual, the individual attributes comprising demographic data, medical data, and individual location data. Further, the computer-implemented method may be configured for determining an individual risk factor based at least on the individual profile data. Responsive to the individual risk factor satisfying a first condition, the computer-implemented method may be configured for generating a first alert indicating the individual risk factor for the individual.

Abstract: A computer implemented method for managing jobs using job processing pools. A computer system receives a job having a job type. The computer system identifies a job processing pool in the job processing pools for running the jobs of the job type, wherein the job processing pool comprises job processors for running the jobs of the job type and wherein another job processing pool in the job processing pools comprises other job processors for running the jobs of a different job type. The computer system runs the job having the job type using a job processor of the job type in the job processing pool for the job type. According to other illustrative embodiments, a computer system and a computer program product for managing jobs are provided. As a result, the illustrative embodiments can provide a technical effect of increasing the performance in running jobs in a computer system in which wait times for running jobs can be reduced.

Abstract: An approach for optimizing storage on a local storage device. The approach receives a cloud resource budget limit and a cloud budget time interval. The approach estimates future cloud resource requests expected to arrive before the end of the cloud budget time interval. The approach calculates definitive and estimated costs of cloud resource usage types. The approach calculates a total estimated resource budget consumption. The approach determines if the total estimated resource budget consumption exceeds the cloud resource budget limit. If the approach determines the cloud resource budget limit is not exceeded, then the approach outputs a set of existing unfulfilled cloud resource requests for fulfillment. If the approach determines the cloud resource budget limit is exceeded, then the approach outputs a subset of set of existing unfulfilled cloud resource requests that do not exceed the cloud resource budget limit for fulfillment.

Abstract: An approach for estimating future cloud resource requests. The approach receives information defining a present budget interval. The approach analyzes a cloud resource request database based on entry times in respective past budget intervals occurring within a remaining time in the present budget interval. The approach creates estimates of future expected cloud resource requests based on the analysis.

Abstract: A computer-implemented method for vehicle parking analysis and identification is disclosed. The computer-implemented method includes determining one or more parking preferences and one or more parking requirements of a user. The computer-implemented method includes determining one or more parking spaces based on comparing the one or more ranked parking preferences and the one or more ranked parking requirements of the user to parking data associated with one or more available parking spaces. The computer-implemented method includes generating a parking space recommendation, wherein the parking space recommendation includes the one or more optimal parking spaces selected from the one or more available parking spaces.

Abstract: Provided are a computer program product, system, and method for estimating resource requests for workloads to offload to host systems in a computing environment. A calculation is made required resources of computational resources required to complete processing a plurality of unfinished workloads that have not completed. A determination is made of allocated resources that are not yet provisioned to workloads. The required resources are reduced by the allocated resources not yet provisioned to determine resources to provision. The resources to provision for the unfinished workloads are requested.

Abstract: Nodes of a weighted tree each have their own weight. A normalized weight of a node, relative to other nodes in the tree, is determined based on a proportional weight of the node and a lesser unique sum of the node, as well as those of the node's parents and grandparents, up to a root of the tree. The proportional weight and lesser unique sum of a given node depend only on the unique weights of the sibling group including the given node. Thus, if a weight is modified, the normalized weight can be updated without necessarily recalculating the entire tree.