Abstract: Embodiments of the present invention provide an apparatus comprising a body including a cavity for storing one or more packages, and a conveyor belt disposed above a top surface of the body. The belt is shaped to receive one or more packages, and the belt is controllable to rotate a package placed on the belt either from the top surface to the cavity for storage or from the cavity to the top surface for dispatch. A package comprises at least one of a drone and a payload transported by the drone. The apparatus further comprises a landing mechanism for stabilizing a drone landing on the apparatus.

Abstract: One embodiment provides a method comprising receiving a flight plan request for a drone. The flight plan request comprises a drone identity, departure information, and arrival information. The method further comprises constructing a modified flight plan for the drone based on the flight plan request, wherein the modified flight plan represents an approved, congestion reducing, and executable flight plan for the drone, and the modified flight plan comprises a sequence of four-dimensional (4D) cells representing a planned flight path for the drone. For each 4D cell of the modified flight plan, the method further comprises attempting to place an exclusive lock on behalf of the drone on the 4D cell, and in response to a failure to place the exclusive lock on behalf of the drone on the 4D cell, rerouting the modified flight plan around the 4D cell to a random neighboring 4D cell.

Abstract: Embodiments of the present invention provide a method comprising receiving a task set comprising multiple tasks, receiving operational information identifying one or more operating characteristics of multiple drones, and obtaining an initial heuristic ordering of the multiple tasks based on the operational information and the climate information. Each task has a corresponding task location. The method further comprises scheduling the multiple tasks to obtain a final ordering of the multiple tasks. The final ordering represents an order in which the multiple tasks are scheduled, and the final ordering may be different from the initial heuristic ordering.

Abstract: One embodiment provides a method comprising maintaining a multi-dimensional data structure partitioned into cells utilizing a tree data structure (“tree”) comprising intervals for each dimension of a multi-dimensional space. To partition an interval for a node of the tree into multiple subintervals, multiple leaf nodes (“leaves”) are generated, each leaf descending from the node. To merge multiple intervals for multiple nodes of the tree, a parent node (“parent”) and multiple leaves descending from the parent are generated, the parent and the leaves are time constrained, and the leaves are scheduled for a merger. When transient data in cells included in a list that corresponds to a leaf scheduled for merger expires, each cell in the list is converted into a cell for inclusion in a different list corresponding to a parent of the leaf, each leaf of the parent removed, and the parent turned into a leaf.

Abstract: Embodiments of the present invention provide a method comprising maintaining historical meeting information, receiving an event data stream corresponding to a meeting, and delaying confirmation of an assignment of a meeting room for the meeting for a period of delay defined by a confirmation condition to predict a number of in-person attendees at the meeting based on the event data stream and the historical meeting information. The meeting room is tentatively assigned to the meeting based on the predicted number of in-person attendees. The method further comprises sending confirmation of the assignment of the meeting room for the meeting to at least one invitee only after the period of delay has elapsed.

Abstract: Embodiments of the present invention provide a method for detecting a temporal change of name associated with performance data. The method comprises receiving at least one candidate name replacement pair comprising a pair of names. The method further comprises, in a training stage, for each known name replacement pair included in the performance data, determining a window of time covering a most recent appearance of a first name of the known name replacement pair. The window of time is determined based on quantitative features of a time series model comprising performance data for the first name and a second name of the known name replacement pair. The method further comprises, in the training stage, training a machine learning classifier based on quantitative features computed using a portion of the performance data for the first name and the second name, where the portion is within the window of time determined.

Abstract: Methods, systems, and articles of manufacture for prioritizing proposal development under resource constraints are provided herein.

Abstract: Disclosed are methods and systems for identifying and visualizing the patterns of work transfers for service delivery using financial data. Within a service firm, work is often transferred from one delivery center to another, which results in additional costs and delays in service delivery. To control unnecessary work transfers, sustained patterns of work transfer are identified so that steps can be taken to limit their occurrence. The disclosed methods and systems analyze the relations among the costs transferred from one location to another.

Abstract: Embodiments of the present invention provide a system, method and computer program product for extrapolating a time series. A method comprises receiving multiple sequences of data values over time. Each sequence of data values is partitioned into a corresponding plurality of segments comprising at least one rising segment that rises to a peak data value of the sequence of data values and at least one falling segment that falls to a trough data value of the sequence of data values. For each sequence of data values, a corresponding sequence of segments that rise and fall alternately is generated based on a corresponding plurality of segments for the sequence of data values. An aggregated sequence of segments is generated by aggregating each sequence of segments generated. The aggregated sequence of segments represents a typical model for the sequences of data values.

Abstract: Embodiments of the present invention provide a system, method and computer program product for forecasting a time series based on actuals and a plan. A method comprises generating a first and a second sequence of segments that rise and fall alternately based on a first and a second sequence of data values over time, respectively. The first and second sequence of data values represent actual data for an ongoing project and estimated data for a planned project, respectively. The method further comprises aligning at least one segment of the second sequence of segments with at least one segment of the first sequence of segments, and adjusting the estimated data by replacing at least one segment of the second sequence of segments with a scaled version of at least one corresponding aligned segment of the first sequence of segments. The scaled version maintains an estimated total for the planned project.

Abstract: Embodiments of the present invention provide a system, method and computer program product for selecting representative models. A method comprises generating a first data model representing a first aggregation level, and generating multiple additional data models. Each additional data model represents a lower aggregation level than the first data model. For each additional data model, a corresponding score is determined. For each lower aggregation level, a corresponding combined score is determined based on two or more highest scoring additional data models representing the lower aggregation level. The method further comprises reporting a second aggregation level and a set of data models. The second aggregation level is a lower aggregation level having the highest combined score over all other lower aggregation levels. The set of data models comprises two, or more, highest scoring additional data models representing the second aggregation level.

Abstract: Embodiments of the present invention provide a system, method and computer program product for generating a succinct approximate representation of a time series. A method comprises determining at least one peak data value and at least one trough data value of an input series comprising a sequence of data values over time. The input series is partitioned into multiple segments comprising at least one rising segment that rises to a peak data value and at least one falling segment that falls to a trough data value. A sequence of segments that rise and fall alternately is generated based on the segments. A sequence of totals representing a succinct approximate representation of the input series is generated. Each total comprises a sum of data values for a corresponding segment of the sequence of segments.

Abstract: Disclosed are methods and systems for identifying and visualizing the patterns of work transfers for service delivery using financial data. Within a service firm, work is often transferred from one delivery center to another, which results in additional costs and delays in service delivery. To control unnecessary work transfers, sustained patterns of work transfer are identified so that steps can be taken to limit their occurrence. The disclosed methods and systems analyze the relations among the costs transferred from one location to another.

Abstract: Systems and methods for are described herein for transforming project management application representations into business process models. An aspect provides for receiving at least one portion of a project management application representation; and generating at least one business process by applying at least one transformation pattern to the at least one project management representation. Other embodiments and aspects are also provided herein.