Abstract: Methods, systems, and computer program products for scheduling crop transplantations are provided herein. A method includes determining one or more lifecycle constraints associated with a given crop via analysis of crop data; determining one or more cultivation conditions constraints associated with cultivating the given crop via analysis of cultivation conditions data; determining one or more weather forecast constraints associated with a given geographic area via analysis of weather forecast data; and generating a transplantation schedule for the given crop in the given geographic area based on determining a fit across (i) the one or more lifecycle constraints, (ii) the one or more cultivation conditions constraints, and (iii) the one or more weather forecast constraints.

Abstract: One embodiment provides a method for determining at least one recommended vehicular travel route, the method including collecting a plurality of travel route inputs from a plurality of sources, relative to a travel route comprising a starting point and an ending point; determining at least one travel route recommendation by (i) assessing the collected plurality of travel route inputs and (ii) taking in to consideration vehicle emission impact parameters; and tracking vehicle adherence. Other variants and embodiments are broadly contemplated herein.

Abstract: Methods, systems, and computer program products for dynamic batch sizing for inferencing of deep neural networks in resource-constrained environments are provided herein. A computer-implemented method includes obtaining, as input for inferencing of one or more deep neural networks, (i) an inferencing model and (ii) one or more resource constraints; computing, based at least in part on the obtained input, a set of statistics pertaining to resource utilization for each of multiple layers in the one or more deep neural networks; determining, based at least in part on (i) the obtained input and (ii) the computed set of statistics, multiple batch sizes to be used for inferencing the multiple layers of the one or more deep neural networks; and outputting, to at least one user, the determined batch sizes to be used for inferencing the multiple layers of the one or more deep neural networks.

Abstract: Methods, systems, and computer program products for suggesting sensor placements are provided herein.

Abstract: Methods and arrangements for automating weather model configurations. Characteristics of a target geographical area are received, as are a plurality of existing weather model configurations which are implemented for undertaking weather modeling in other geographical areas. A subset of the existing weather model configurations is selected, the subset comprising configurations corresponding to geographical areas having characteristics similar to the characteristics of the target area. A weather model is run with respect to each configuration in the subset of existing weather model configurations. Based on the running of a weather model with respect to each configuration, an output set of weather model configurations is selected for undertaking weather modeling in the target area.

Abstract: Methods, systems, and computer program products for suggesting sensor placements are provided herein.

Abstract: One embodiment provides a method for determining at least one recommended vehicular travel route, the method including collecting a plurality of travel route inputs from a plurality of sources, relative to a travel route comprising a starting point and an ending point; determining at least one travel route recommendation by (i) assessing the collected plurality of travel route inputs and (ii) taking in to consideration vehicle emission impact parameters; and tracking vehicle adherence. Other variants and embodiments are broadly contemplated herein.

Abstract: Methods and arrangements for performing synchronized collective operations. Communication calls are accepted from at least two distinct processor groups. Edge disjoint spanning paths are created over a collective comprising the processor groups, and the spanning paths are assigned to the processor groups to facilitate communication within each processor group.

Abstract: Methods and arrangements for performing synchronized collective operations. Communication calls are accepted from at least two distinct processor groups. Edge disjoint spanning paths are created over a collective comprising the processor groups, and the spanning paths are assigned to the processor groups to facilitate communication within each processor group.

Abstract: Methods, systems, and computer program products for scheduling crop transplantations are provided herein. A method includes determining one or more lifecycle constraints associated with a given crop via analysis of crop data; determining one or more cultivation conditions constraints associated with cultivating the given crop via analysis of cultivation conditions data; determining one or more weather forecast constraints associated with a given geographic area via analysis of weather forecast data; and generating a transplantation schedule for the given crop in the given geographic area based on determining a fit across (i) the one or more lifecycle constraints, (ii) the one or more cultivation conditions constraints, and (iii) the one or more weather forecast constraints.

Abstract: Methods, systems, and articles of manufacture for generating an ensemble of forecasting models are provided herein. A method includes identifying a given environmental event from multiple items of input data; estimating an accuracy value for each of multiple forecasting models applied to an environmental event related to the given environmental event based on historical data; computing a cost and one or more resource requirements for each of the multiple forecasting models; and determining an ensemble of one or more of the multiple forecasting models to apply to the given environmental event based on (i) said estimated accuracy value for each of the multiple forecasting models, and (ii) said cost and said one or more resource requirements for each of the multiple forecasting models.

Abstract: Techniques for transferring a matrix for performing one or more operations are provided. The techniques include applying a permutation on at least one of one or more columns and one or more rows of a matrix to group each of at least one of one or more columns and one or more rows of the matrix with a same alignment, blocking at least one of the grouped columns and grouped rows, and performing one or more operations on each matrix block.

Abstract: A computer-implemented method of load balancing including calculating an expected cost set associated with an application-specific task of an application executing on a processing resource in a cloud computing environment, and communicating the expected cost set from the processing resource to a cloud management system. Resource mapping of applications currently executing in the cloud computing environment are retrieved, the application-specific task is assigned to a specific computational resource in the cloud computing environment based on the expected cost set and the resource mapping of applications currently executing in the cloud computing environment. A task to VM (virtual machine) assignment is determined based on the assignment of the application-specific task to the specific computational resource. The task to VM assignment is transferred from the cloud management system to the application executing on the processing resource in the cloud computing environment.

Abstract: A non-transitory computer-implemented method of load balancing includes calculating an expected cost set associated with an application-specific task of an application executing on a processing resource in a cloud computing environment, and communicating the expected cost set from the processing resource to a cloud management system. Resource mapping of applications currently executing in the cloud computing environment are retrieved, and the application-specific task is assigned to a specific computational resource in the cloud computing environment based on the expected cost set and the resource mapping of applications currently executing in the cloud computing environment. A task to VM (virtual machine) assignment is determined based on the assignment of the application-specific task to the specific computational resource. The task to VM assignment is transferred from the cloud management system to the application executing on the processing resource in the cloud computing environment.

Abstract: Methods and arrangements for automating weather model configurations. Characteristics of a target geographical area are received, as are a plurality of existing weather model configurations which are implemented for undertaking weather modeling in other geographical areas. A subset of the existing weather model configurations is selected, the subset comprising configurations corresponding to geographical areas having characteristics similar to the characteristics of the target area. A weather model is run with respect to each configuration in the subset of existing weather model configurations. Based on the running of a weather model with respect to each configuration, an output set of weather model configurations is selected for undertaking weather modeling in the target area.

Abstract: Methods and arrangements for performing synchronized collective operations. Communication calls are accepted from at least two distinct processor groups. Edge disjoint spanning paths are created over a collective comprising the processor groups, and the spanning paths are assigned to the processor groups to facilitate communication within each processor group.

Abstract: Methods and arrangements for performing synchronized collective operations. Communication calls are accepted from at least two distinct processor groups. Edge disjoint spanning paths are created over a collective comprising the processor groups, and the spanning paths are assigned to the processor groups to facilitate communication within each processor group.

Abstract: A method of generating an image includes the step of obtaining captured data characterizing an object. The method also includes the step of reconstructing a spatio-temporal image of the object based on the captured data, the spatio-temporal image comprising a plurality of spatial images in respective time intervals, with at least a given one of the spatial images in one of the time intervals being reconstructed using captured data from a frame associated with that time interval and captured data associated with one or more additional frames associated with other time intervals. The method further includes the step of outputting the spatio-temporal image. The obtaining, reconstructing and outputting steps are performed by a processing device comprising a processor coupled to a memory.

Abstract: A spatio-temporal image of an object is reconstructed based on captured data characterizing the object. The spatio-temporal image comprises a plurality of spatial images in respective time intervals, and at least a given one of the spatial images in one of the time intervals is reconstructed using not only captured data from a frame associated with that time interval but also captured data associated with one or more additional frames associated with other time intervals. The spatio-temporal image may be reconstructed by iteratively obtaining a solution to a minimization or maximization problem in a sparse domain and transforming the solution to an image domain. The transformation between the sparse domain and the image domain may utilize a spatio-temporal transformation implemented using a plurality of basis functions, one or more of which may be determined at least in part based on secondary information associated with the imaged object.

Abstract: A non-transitory computer-implemented method of load balancing includes calculating an expected cost set associated with an application-specific task of an application executing on a processing resource in a cloud computing environment, and communicating the expected cost set from the processing resource to a cloud management system. Resource mapping of applications currently executing in the cloud computing environment are retrieved, and the application-specific task is assigned to a specific computational resource in the cloud computing environment based on the expected cost set and the resource mapping of applications currently executing in the cloud computing environment. A task to VM (virtual machine) assignment is determined based on the assignment of the application-specific task to the specific computational resource. The task to VM assignment is transferred from the cloud management system to the application executing on the processing resource in the cloud computing environment.